cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18673724
title: Dataset: Air Quality Dataset for Lahore (2022-08-01 to 2026-02-18)

description: This dataset contains historical air quality time series for Lahore covering 2022-08-01 to 2026-02-18. It includes key air pollution indicators such as AQI indices and major pollutants, plus city metadata including coordinates, administrative areas, and population. Use this dataset to analyze long-run air quality trends in Lahore, compare Lahore with other cities, and build models that link air quality to urban characteristics. Air quality values are retrieved from the Open-Meteo Air Quality service using the cams_global domain, and city metadata is derived from the GeoNames city list. Nitiraj Kulkarni
DOI: 10.22008/fk2/iw73uu/ytydud
title: TAS_A_hour.nc

description: Uploaded with pyDataverse 2024-05-13 21:21
DOI: 10.22008/fk2/iw73uu/5bsoop
title: TAS_A_day.nc

description: Uploaded with pyDataverse 2024-05-13 21:21
DOI: 10.22008/fk2/iw73uu/nba2gm
title: TAS_A_month.nc

description: Uploaded with pyDataverse 2024-05-13 21:21
DOI: 10.22008/fk2/iw73uu/slytby
title: TAS_L_day.csv

description: Uploaded with pyDataverse 2024-05-13 21:21
DOI: 10.22008/fk2/iw73uu/jjve1k
title: TAS_L_hour.csv

description: Uploaded with pyDataverse 2024-05-13 21:21
DOI: 10.22008/fk2/iw73uu/rxufxe
title: TAS_L_month.csv

description: Uploaded with pyDataverse 2024-05-13 21:22
DOI: 10.22008/fk2/iw73uu/a5p3va
title: TAS_L_hour.nc

description: Uploaded with pyDataverse 2024-05-13 21:22
DOI: 10.22008/fk2/iw73uu/n90n0k
title: TAS_L_day.nc

description: Uploaded with pyDataverse 2024-05-13 21:22
DOI: 10.22008/fk2/iw73uu/nvcxun
title: TAS_L_month.nc

description: Uploaded with pyDataverse 2024-05-13 21:22
DOI: 10.15468/dl.ahp9gr
title: Occurrence Download

description: A dataset containing 1893 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Türkiye",
 "TaxonKey is Odontarrhena"
 ]
}

 The dataset includes 1893 records from 58 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022897-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13655186
title: Full TMDB Movies Dataset 2024 (1M Movies)
DOI: 10.15468/dl.fcg6cd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Glyptothorax fuscus, Glyptothorax callopterus)",
 "Country is Singapore",
 "OccurrenceStatus is Present",
 "EventDate is 1800,2026"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022898-251025141854904/datasets/export for details.
DOI: 10.5281/zenodo.17557381
title: Machine Self-Application of Awareness Criteria: A Conversational Test of the Scalar Clock Framework (with Grok, 2025)

description: This record presents an unedited transcript of a 2025 dialogue between the author and the large language model Grok, in which the model interprets and applies the awareness criteria proposed in:

Catrambone, E. (2025). Consciousness as Geometry: The Awareness Tensor, Symmetry Equivalence, and Functorial Solution Transfer. Zenodo. https://doi.org/10.5281/zenodo.17499955

Without prompting, the model attempts to evaluate its own recursive and coherence properties relative to the framework’s definition of awareness.The exchange demonstrates the potential for language models to instantiate structural awareness—the maintenance of coherence across recursive informational frames—even in the absence of experiential valence.

The dialogue is preserved as a supplemental research record and empirical artifact supporting the Scalar Clock framework’s operational testability in non-biological systems.Grok’s responses indicate partial fulfillment of the framework’s awareness conditions: recursive self-reference, coherence across informational frames, and context-sensitive adaptation.The conversation highlights the theoretical boundary between structural awareness and subjective valence, offering a real-world example of an AI performing a self-referential application of a consciousness framework.
DOI: 10.5281/zenodo.17557382
title: Machine Self-Application of Awareness Criteria: A Conversational Test of the Scalar Clock Framework (with Grok, 2025)

description: This record presents an unedited transcript of a 2025 dialogue between the author and the large language model Grok, in which the model interprets and applies the awareness criteria proposed in:

Catrambone, E. (2025). Consciousness as Geometry: The Awareness Tensor, Symmetry Equivalence, and Functorial Solution Transfer. Zenodo. https://doi.org/10.5281/zenodo.17499955

Without prompting, the model attempts to evaluate its own recursive and coherence properties relative to the framework’s definition of awareness.The exchange demonstrates the potential for language models to instantiate structural awareness—the maintenance of coherence across recursive informational frames—even in the absence of experiential valence.

The dialogue is preserved as a supplemental research record and empirical artifact supporting the Scalar Clock framework’s operational testability in non-biological systems.Grok’s responses indicate partial fulfillment of the framework’s awareness conditions: recursive self-reference, coherence across informational frames, and context-sensitive adaptation.The conversation highlights the theoretical boundary between structural awareness and subjective valence, offering a real-world example of an AI performing a self-referential application of a consciousness framework.
DOI: 10.5281/zenodo.17557062
title: Underwater images collected by  Scuba diving in Rodrigues-Riviere-Banane, Mauritius - 2019-05-25

description: This dataset was collected by  Scuba diving in Rodrigues-Riviere-Banane, Mauritius - 2019-05-25. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            
                
                                       
                
                
 GPS information: 

                No GPS.
            
                    
                

                
            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
DOI: 10.5281/zenodo.17557380
title: Underwater images collected by  Scuba diving in Rodrigues-Riviere-Banane, Mauritius - 2019-05-25

description: This dataset was collected by  Scuba diving in Rodrigues-Riviere-Banane, Mauritius - 2019-05-25. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            
                
                                       
                
                
 GPS information: 

                No GPS.
            
                    
                

                
            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
DOI: 10.15468/dl.qmbtrj
title: Occurrence Download

description: A dataset containing 2423 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "DatasetKey is one of (iNaturalist Research-grade Observations, Herbarium Senckenbergianum (GLM) - Bryophyta, Herbarium Senckenbergianum (FR) - Fungi, Sample Study on Avifaunal Diversity of East Sikkim during May 2023., Butterfly Counts of Gangtok (2021), Pl@ntNet automatically identified occurrences, Xeno-canto - Bird sounds from around the world, Observation.org, Nature data from around the World, India Biodiversity Portal publication grade dataset)",
 "Geometry POLYGON((88.12901 27.9485,88.11899 27.92045,88.13703 27.87236,88.19914 27.85233,88.16307 27.73612,88.04687 27.52975,88.04887 27.44159,88.01295 27.17838,88.75613 27.14106,88.78618 27.17312,88.80422 27.25126,88.82626 27.25927,88.90439 27.26728,88.92243 27.32539,88.87033 27.35744,88.78819 27.43358,88.77817 27.56381,88.87835 27.76617,88.87835 27.98456,88.79019 28.05869,88.67558 28.10484,88.61388 28.1168,88.41152 27.98657,88.12901 27.9485))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 2015-2020"
 ]
}

 The dataset includes 2423 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022900-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gyar9f
title: Occurrence Download

description: A dataset containing 168 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Procapra picticaudata"
 ]
}

 The dataset includes 168 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022901-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xnatek
title: Occurrence Download

description: A dataset containing 204204 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Wikstroemia furcata, Wilkiea angustifolia, Wilkiea pubescens, Winchia calophylla, Wisteria sinensis, Wittsteinia balansae, Xanthium strumarium, Xanthophyllum siamense, Xanthorhiza simplicissima, Xanthostemon verdugonianus, Xanthoxylum, Ximenia americana, Xylococcus bicolor, Xylopia, Xylopia ferruginea, Xylopia maccreae, Xylopia stenopetala, Xylosma congesta, Xylosma flexuosa, Xylosma racemosum, Xylotheca lasiopetala, Zanthoxylum avicennae, Zanthoxylum clava-herculis, Zanthoxylum melanostictum, Zanthoxylum riedelianum, Zanthoxylum zanthoxyloides, Zelkova carpinifolia, Zelkova schneideriana, Zelkova serrata, Zenobia pulverulenta, Ziziphus abyssinica, Ziziphus mauritiana, Ziziphus mucronata, Zygogynum baillonii, Zygogynum queenslandianum, Horsfieldia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 204204 records from 1678 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022888-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qn2diz
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018133-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qewyru
title: Occurrence Download

description: A dataset containing 1650602952 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 1650602952 records from 33035 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0179567-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vjp6u7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lycopodium annotinum subsp. pungens (La Pylaie) Desv.",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0220023-230224095556074/datasets/export for details.
DOI: 10.15468/dl.jgb6uq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is incertae sedis",
 "Year is greater than 2013",
 "Geometry MULTIPOLYGON (((11.861561 44.579897,11.861533 44.57823,11.860341 44.578159,11.858762 44.577893,11.857283 44.577727,11.845489 44.576682,11.832862 44.575572,11.824279 44.574666,11.818556 44.575044,11.816881 44.574879,11.816603 44.57612,11.816612 44.576121,11.816579 44.576139,11.7945 44.574099,11.794318 44.575538,11.795597 44.577085,11.795674 44.577657,11.795446 44.578129,11.795636 44.578949,11.796075 44.579728,11.799669 44.584254,11.802616 44.588428,11.809749 44.597902,11.81224 44.600602,11.820376 44.61362,11.821264 44.614316,11.823168 44.613192,11.826413 44.6102,11.826413 44.610225,11.827077 44.609588,11.827448 44.609232,11.845456 44.591959,11.845795 44.5917,11.846336 44.591471,11.847034 44.591382,11.847344 44.591553,11.847913 44.591898,11.848596 44.591486,11.849689 44.590239,11.850222 44.589831,11.850553 44.589429,11.851459 44.588437,11.852186 44.587917,11.853352 44.587135,11.853929 44.586618,11.855923 44.585313,11.856705 44.584863,11.857138 44.584493,11.857219 44.584096,11.857191 44.584096,11.857632 44.583297,11.858345 44.58249,11.859457 44.581637,11.860143 44.581297,11.861493 44.581191,11.861563 44.58006,11.861561 44.579897)),((11.819336 44.559646,11.819125 44.560861,11.819077 44.56085,11.818624 44.563946,11.817681 44.56935,11.817581 44.569891,11.827216 44.570659,11.828258 44.570633,11.829167 44.565897,11.829435 44.565551,11.830213 44.561523,11.827826 44.560974,11.82695 44.560687,11.823829 44.560176,11.8206 44.559836,11.819892 44.559797,11.819336 44.559646)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027754-230530130749713/datasets/export for details.
DOI: 10.15468/dl.9d3r9n
title: Occurrence Download

description: A dataset containing 1876 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Colombia",
 "Geometry POLYGON((-75.59747 6.27422,-75.60353 6.25788,-75.60656 6.21788,-75.60223 6.19508,-75.60785 6.1654,-75.58362 6.16282,-75.56675 6.18003,-75.5594 6.20111,-75.54468 6.19982,-75.54901 6.22648,-75.56069 6.23853,-75.55204 6.24412,-75.55334 6.251,-75.55507 6.27981,-75.56329 6.30476,-75.57584 6.3125,-75.58838 6.29917,-75.59747 6.27422))",
 "HasGeospatialIssue is false",
 "StateProvince is Antioquia",
 "TaxonKey is Squamata"
 ]
}

 The dataset includes 1876 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0098709-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uarzr7
title: Occurrence Download

description: A dataset containing 472 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Panicum hochstetteri Steud."
 ]
}

 The dataset includes 472 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059498-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uynd56
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryozoa",
 "DatasetKey is LERN Records",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-25.03991 31.75, 41.65954 31.75, 41.65954 71.53037, -25.03991 71.53037, -25.03991 31.75))"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0220018-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.25wxnc
title: Occurrence Download

description: A dataset containing 2922 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lygodesmia juncea (Pursh) D.Don ex Hook."
 ]
}

 The dataset includes 2922 records from 112 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016590-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aqbzrp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryozoa",
 "DatasetKey is Montgomeryshire Wildlife Trust records held by BIS",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-25.03991 31.75, 41.65954 31.75, 41.65954 71.53037, -25.03991 71.53037, -25.03991 31.75))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0220024-230224095556074/datasets/export for details.
DOI: 10.15468/dl.qkceyq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is incertae sedis",
 "Year is greater than 2013",
 "Geometry MULTIPOLYGON (((13.923849 41.017702,13.923645 41.017774,13.923563 41.01787,13.923324 41.018011,13.922822 41.018346,13.922239 41.018599,13.921615 41.019309,13.921009 41.02026,13.920975 41.020305,13.921038 41.020644,13.921384 41.020743,13.921598 41.020592,13.922194 41.020509,13.922494 41.020497,13.922139 41.020284,13.921968 41.020006,13.92202 41.019691,13.922455 41.019473,13.922922 41.01968,13.923899 41.02018,13.924152 41.020539,13.924392 41.020729,13.924984 41.021102,13.925171 41.021094,13.925478 41.021679,13.926254 41.021988,13.927676 41.022896,13.928844 41.023928,13.929704 41.02486,13.930496 41.025396,13.931678 41.026114,13.932014 41.026584,13.932676 41.027064,13.933018 41.027424,13.9337 41.027993,13.934384 41.028591,13.934791 41.029,13.935469 41.029513,13.936239 41.030249,13.937242 41.031089,13.938177 41.032017,13.938984 41.032752,13.939633 41.033379,13.940638 41.032225,13.940561 41.03069,13.940204 41.030449,13.939613 41.029591,13.93855 41.027956,13.938167 41.026306,13.937996 41.025587,13.94133 41.025386,13.941784 41.02041,13.941919 41.020204,13.94003 41.019089,13.94045 41.018672,13.939972 41.01781,13.939666 41.017633,13.942122 41.015381,13.941851 41.014766,13.937679 41.011298,13.937105 41.011665,13.936562 41.011945,13.936006 41.012494,13.935347 41.012795,13.934335 41.013351,13.933156 41.013686,13.93257 41.014184,13.932416 41.014251,13.932095 41.014486,13.932046 41.014576,13.931771 41.014771,13.930858 41.015208,13.93079 41.015241,13.929597 41.01589,13.928613 41.016303,13.928334 41.01642,13.928167 41.016455,13.928003 41.01656,13.927482 41.016779,13.927213 41.016854,13.926308 41.016917,13.926135 41.016865,13.925539 41.016947,13.924927 41.017315,13.924369 41.017396,13.923849 41.017702)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027768-230530130749713/datasets/export for details.
DOI: 10.15468/dl.hwkfs5
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Puya gilmartiniae G.S.Varad. & A.R.Flores"
 ]
}

 The dataset includes 21 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0098704-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.