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Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | historic election result stun world new private eye pic twitter com megtj nbu | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | haloo kak aku buka jasa eye make unity nanti niih boleh tanya tanya dulu untuk porto lengkapnya bisa liat di instagram kami di hegobeauty yaa co xhatvbj g | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | trad atualiza da wonchae bstage paz divirta se queenzeye pic twitter com zuh cmolf | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | beautiful eye color co cjkja astl | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | haloo kak aku buka jasa eye make unity nanti niih boleh tanya tanya dulu untuk porto lengkapnya bisa liat di instagram kami di hegobeauty yaa co v yvcv oi | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | evil eye real shaykh qomarudeen yunus akorede check attach thread rest video co xxu u xame | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | queenz eye tokyo concert damin queenzeye pic twitter com eylwbfybbo | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | check interface experiment eye gaze multitouch feature recent talk origin gaze pinch vr combine finger chord gaze base target selection seriously smooth fast paced sort ly xrgdi co zjcmhmf w | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye tiger logline base true story united states marine young son overcome blindness eye cancer become golf sensation capture heart million turn adversity inspiration screenpit fea sere drdy fa q wrdis pic twitter com anfjxqmlxr | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | see number eye test pic twitter com yvgzwlhfnr | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | queenz eye tokyo concert hannah queenzeye pic twitter com cas qanpg | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | even sef finish know today like okro tomorrow egusi enter eye weekend without afang | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | ahyoon via twitter obrigada por queenzeye pic twitter com xiovxnksae | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | queenz eye tokyo concert damin queenzeye pic twitter com oytedsenzb | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye love fan festival eyeloveyou | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | striker sydney lokale speak late goal bidco united make sure catch full int sport eye channel link youtu lw fooy b si co cvtlfnazgn | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | open eyemakeup unity jakarta start k available di venue course sangat rapi dan cantik mau request apapun bisa eye makeup face makeup face paint hair cek langsung katalog di ig kita ya wa co nykfk kxkl | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye injury work often preventable occur due flying particle chemical exposure tool equipment uv radiation stay vigilant prioritize safety use proper protective measure avoid workplace eye injury workplacesafety pic twitter com yyevlj tsi | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | myste mean anthony anthony burns doll eye au forget memory art digitalart au dolleyegame dolleye forgottenmemory pic twitter com yubrnar | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | lot people fully get sick bt actually act operate camera look like pound strapped avoid buzz lens direct eye contact ft face talent | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | fluorescencefriday teaser presentation sunday monday seattle simultaneous imaging blood flow fluorescent mitochondria living retina look author jesse schallek derek power co cyet w rqz | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | steve mccue unique dyslexic eye blog assistive technology sdyslexia blogspot com assist another unique dyslexic blog steve uniquedyslexic mccue please share among follower feedback comment always welcome co qwrnhisbc | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | see eye see optometrist clara two love eye lifelong fave boyband button fly guy return home organize santa spectacle spectacular meet corbin stranger feel oh familiar screenpit roco cov cdnwriter pic twitter com v knh zzd | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | queenz eye w tokyo concert live wonchae queenzeye pic twitter com h rrfbu | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | cast cold eye paperback today discuss jimmy dreghorn novel cwa dagger winner brilliant april th waterstone com event robbie | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | corinthians new international version however write eye see ear hear human mind conceive thing god prepare love pic twitter com v dgm ee | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | jpn sub eye love chaejonghyeop imbc click plz youtu sghut r co hqvfw n eq | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | comeback vai vir segundo f que estavam concerto hoje ceo grupo esteve presente em quio nos ltimos dias e ir voltar para cor ia para come ar os planejamentos para pr ximo comeback queenz eye queenzeye pic twitter com ufkfsn kqk | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | miss special mini game lenscrafter eye odyssey roblox immerse fashionable world eyewear several room level feature luxury house iconic style come experience join we ms spr ly cbuua co hjldehtox | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | yo indian boy w ou chronic poor vision nystagmus note od sudden dim exam show ou hypopigmente iris fundi od typical irido retino choroidal coloboma assc w total retinal detachment dx w ocular albinism retina eyetwitter ow ly c iq rt co jriwofj k | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | cvi cause variety visual problem range mild severe common symptom condition include photophobia poor social gaze visual field loss clumsiness trouble smooth eye movement find hard see noisy pic twitter com fn lnji | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | richly deserve | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye sol market cap make wave dexscreener com solana dbw qx contract address mawnfagdczqmhqh fvt f zzlqxpwgjpal zutpump follow part eye journey eye meme sol solana co ytrl ph ah | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | know eye ultimate photographer capture moment blink eye explore fascinating fact incredible ability vision we eyefact didyouknow nethrainsights pic twitter com mop xr ah | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | queenz eye tokyo concert queenzeye japan tokyo concert hannah pic twitter com era smd sv | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | queenz eye japan concert still still cover narin queenzeye queenzeyeinjapan thisislove stillwithyou youtube com watch v kpc | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | people go blind uk glaucoma source pic twitter com xvyxdv c | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | levin odhiambo open happen sweden move catch full interview sport eye link youtu u lrncrsku si co q vl ovzu | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | advance optometry commitment global eye care worldoptometryday co ot vrjldxa | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye really like ur stuff | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | need eye catch graphic design create unique aesthetic visual graphic need include poster brochure custom illustration stunning design set apart crowd link fiverr com kqegxq co vkysehvy f | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | like vitamin e vitamin c antioxidant recommend fight age relate eye damage vitamin c rich citrus fruit include lemon orange grapefruit | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | logo thumbnail specialist craft eye catch logo thumbnail elevate content passionate design creativity let make visual stand | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | make inexplicable decision triple entry fee sunday full roster slate cost user enter single lineup move favor dfs pro bat eye pay max entry sicken pic twitter com fvot zm fj | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | kick insightlive breakfast meet gender equity eye care speak inclusion advocacy campaigning climate gender much pic twitter com ekqwoz v | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | nerve back eye connect brain optic nerve send light signal brain see keep healthy get enough nutrient nerve need important example include vitamin b b b mineral copper pic twitter com e dzkpyx | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | see number eye test pic twitter com ui abgjwz | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | see number eye test pic twitter com ui abgjwz | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | enjoy sunny day outside gaze cloud suddenly spot small speck seem move move eye first try blink away thinking might bit dust budge eye floater | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | jun | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | slow missionary x eye contact kiss rty talk exceed position say say | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | sell guy mandola really us bad seller cause mess | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | easy pick doosra without sharp eye see happy team embrace life good moment clearly partnership co vph oaw h | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | oh god get eye roll damn republicans complain government waste turn around waste tax dollar co virdud n l | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye love eyeloveyou eyeloveyou pic twitter com farevmbvay | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | atualiza da damin bstage q n se preocupe sobre meu aniver rio jap minhas unnie deram um parab n muito animado kkkkkkkkkkkkkkkkkkkkkkkkkkkkkk minhas amadas unnies queenzeye co lu wfysxu | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | magnetic clip multipurpose eye glass frame pic twitter com jovjy banh | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | human league heaven martyn ware talk dorset eye dorseteye com human leag co sehpbqtlr | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | human eye structure inside neuroscience co habuoc ipu | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eid mubarak enjoy celebration cherish moment family friend us retina uk eid mubarak eidmubarak eidaladha festivegreeting communityjoy retinauk pic twitter com u fndum fx | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | always think finger perform eye operation get addicted cellphone n stuff | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | unique dyslexic eye podcast youtu aiafj xbqao si via record quite near start lockdown dyslexia work stop hnd hnc course broadcasting think start unique dyslexic eye podcast channel | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | story catch eye think ever see something quite like lg delhi write newspaper column call people delhi virtually vote aap govt could easily write opposition leader almost every raj bhavan | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | huge number police car weymouth seafront tonight least two man handcuff enormous crowd onlooker even police car arrive hope everyone ok pic twitter com vf dqshrxc | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | halo buat temen chilzen sijeuni nctzen yg minat eye full make hair konser unity day nanti bisa book di aku yaa thankyou | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | dolleye dolleyegame kaoushi tag cuz forgor | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | web eye love kinolight com dmr eyeloveyou co xhdtnqkunr | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | kepeing eye twitter com tylerlopezai | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye love eyeloveyou pic twitter com pp rbljz u | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | let make collective effort break habit stare phone tvs laptop without protective measure might seem small investing eye health make big difference long run clear vision tech savvy eye friendly year ahead | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eyetracke | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | queenz eye tokyo concert hannah queenzeye pic twitter com vrttur ibt | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | correlation microperimetry image extensive macular atrophy pseudodrusen like appearance romano francesco md febo et retina p february journals lww com retinajournal retina | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | thank share dream we little bit hope one stay happy healthy matter time queenz eye q spend together precious thank happy year year queenzeye queenzeye co jy ut hnnc | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | cause trachoma primary culprit behind trachoma bacterium chlamydia trachomatis bacterium spread easily overcrowded living condition personal hygiene may compromise fly come contact infect eye discharge also | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | people often overlook importance proper vision sport like training athlete without ensure see properly first build hand eye coordination reaction time skill essential basic vision ignore sportsvision co thizrxgpg | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | awesome funny look gpx retina | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eyeloveyou use chae jonghyeop yoon taeoh nikaido fumi motomiya yuri eye love jdrama edit use sza co za bt hvpz | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | kiss hair eye contrast doe | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | queenzeye tokyo concert queenzeye damin pic twitter com qq oycw | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | cover image contribute | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | amani fawzi md team look double layer sign fovea spare ga find presence thick double layer sign foveal area may play protective role acrc retina macula pic twitter com nkbxi hvds | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | like lammy certainly trust one inch pic twitter com alch hg k | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye ball | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | boy donald gone kick hornet nest proper riled lefty snowflake late truth london town paris trump bang money thank year spineless politician turn blind eye uncontrolle co nhbksdyed | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | we eye love we eyeloveyou | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | expert level side eye | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | unique dyslexic eye podcast youtu aiafj xbqao si via record quite near start lockdown dyslexia work stop hnd hnc course broadcasting think start unique dyslexic eye podcast channel | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | I m begin understand dad swear life none four daughter would marry yoruba man look like tribalism eye clear | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | happy valentine day break heart eye brain neurotwitter eyetwitter aneurysm co rtwsal kq | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | amazing record tamil nadu always stand first eye donation proud tamilian | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye love | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | private eye illustrate reasonable question sentence length give stop oil protestor pic twitter com astsxhfbka | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | private eye illustrate reasonable question sentence length give stop oil protestor pic twitter com astsxhfbka | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | amunra odin eye handofgod pic twitter com maug pka | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | top starmer aide leave new private eye pic twitter com tcnqjfyogr | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye surgery photography capturing view world dr chandra perera general ophthalmologist bunbury busselton eye specialist grow vic coastal town warrnambool pic twitter com irgdxsjlmo | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | go australia names royal comission child abuse public turn blind eye | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye test word see first pic twitter com azrwx htf | Non-Medical |
Classify the given text input into two categories: Medical or Non-Medical, based on the intention of the text and the context in which words are used. Output only the classification type ("Medical" or "Non-Medical") for each input. | eye test word see first pic twitter com azrwx htf | Non-Medical |
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