cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.bp6cf2
title: Occurrence Download

description: A dataset containing 22 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa chinensis",
 "Country is Papua New Guinea",
 "HasCoordinate is true"
 ]
}

 The dataset includes 22 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013352-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zpcfgy
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa chinensis",
 "Country is Myanmar",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013351-250827131500795/datasets/export for details.
DOI: 10.15468/dl.tbx89u
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa chinensis",
 "Country is Singapore",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013353-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5kvr6a
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa chinensis",
 "Country is Timor-Leste",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013354-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.knqt53
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa chinensis",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013355-250827131500795/datasets/export for details.
DOI: 10.15468/dl.nw253f
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa chinensis",
 "Country is Viet Nam",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013356-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57992/nmrxiv.p54
title: Cantharidin (NMRShiftDB datasets)

description: DOI: 10.18716/nmrshiftdb2/20236671

NMRSHIFTDB_ID: 20236671
DOI: 10.57992/nmrxiv.p54.s1292
title: Cantharidin

description: This dataset contains NMR spectra obtained for the sample containing Cantharidin
DOI: 10.57992/nmrxiv.p54.s1292.d5625
title: Cantharidin[1]

description: 1
DOI: 10.57992/nmrxiv.p54.s1292.d5626
title: Cantharidin[2]

description: 2
DOI: 10.57992/nmrxiv.p54.s1292.d5627
title: Cantharidin[3]

description: 3
DOI: 10.57992/nmrxiv.p54.s1292.d5628
title: Cantharidin[4]

description: 4
DOI: 10.57992/nmrxiv.p54.s1292.d5629
title: Cantharidin[5]

description: 5
DOI: 10.57992/nmrxiv.p54.s1292.d5630
title: Cantharidin[6]

description: 6
DOI: 10.5281/zenodo.15346697
title: SNAP v1.0.1 — SNAP–MEG v1.8: Diachronic Constraint Animation Archive

description: This archive contains a validated suite of constraint-driven selection animations produced from the SNAP–MEG v1.8 grammar simulation notebook. All outputs are trace-sealed demonstrations of diachronic constraint dynamics, showcasing lawful latent-to-manifest emergence without optimization, inference, or prediction.

Each animation is grounded in the core SNAP selection grammar:



S_manifest(x, t) = Select(S_potentials, E(x, t), I(x, t)); ℰ(x, t → t+Δt): Diachronic constraint vector transformation


This validates SNAP’s grammar: no training, reward, or optimization — only lawful emergence from constraint compatibility.

Part of the structural lineage of:





SNAP: A Universal Constraint Syntax for Latent-to-Manifest Emergence (https://doi.org/10.5281/zenodo.15279712)




Colour Dynamism v1.5 (https://doi.org/10.5281/zenodo.15241142)



All outputs were generated from snap_activation_data.npz using SHA-sealed simulation notebooks.The raw activation archive is withheld from public release but available upon formal request for institutional validation.

Trace Note:This demo was generated without any tuning, training, or optimization. Constraint weights were heuristically derived from semantic labels. The latent projection is fixed and orthonormal.

Manifest outputs reflect lawful emergence under the SNAP grammar—not fitted scores or inferred preferences. This confirms that the observed activation patterns arise from structure alone.
description: Included Demonstrations





snapmeg_constraint_dynamics.gif Constraint-Governed Potential-to-Manifest — S_manifest points unfold under smooth constraint drift, showcasing SNAP’s non-inferential grammar activation.




snapmeg_constraint_dynamics_select.gif Manifest Selection (Latent-Aligned) — Lawful selection under evolving constraints from a fixed latent pool with vector-matched manifest emergence.




snapmeg_constraint_dynamics_SHUFFLED.gif Control: Shuffled Constraint Field — No coherent emergence; constraint mismatch leads to structural noise. Demonstrates SNAP’s falsifiability.


snapmeg_constraint_diachronic_select.gif Diachronic Field Selection — Latent field drifts over time; constraint vectors interpolate diachronically; emergence aligns with dynamic E/I trajectory.



snapmeg_vector_comparison.gif SNAP vs Random Projection (Side-by-Side) — Vector field transitions reveal alignment under SNAP vs disordered pseudo-manifestation from random projection.
DOI: 10.15468/dl.xj5twn
title: Occurrence Download

description: A dataset containing 171 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (China, Viet Nam, Lao People’s Democratic Republic, Myanmar)",
 "TaxonKey is Amomum villosum"
 ]
}

 The dataset includes 171 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013357-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2wt89p
title: Occurrence Download

description: A dataset containing 31 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa panicea",
 "Country is El Salvador",
 "HasCoordinate is true"
 ]
}

 The dataset includes 31 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013360-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pgurck
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa panicea",
 "Country is Czechia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013359-250827131500795/datasets/export for details.
DOI: 10.15468/dl.sa796t
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa panicea",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 24 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013358-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15151/esrf-dc-2228781165
title: Data: Growth evolution in calcium carbonate microparticles involving mixed vaterite-aragonite structures

description: Coherent diffraction imaging with wide-angle X-ray diffraction (CXDI-WAXD) was used to investigate CaCO3 microparticles crystallized under varied temperatures. 3D tomographic reconstructions revealed distinct density variations, showing particles where vaterite and aragonite coexist. This indicates an intermediate growth stage between early vaterite and later aragonite, offering deeper insight into the morphology structure relationship in CaCO3 polymorph evolution.
DOI: 10.15468/dl.jv7nad
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa panicea",
 "Country is Honduras",
 "HasCoordinate is true"
 ]
}

 The dataset includes 18 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013363-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.89zdsc
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa panicea",
 "Country is Guatemala",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013362-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4ht5p8
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Leptochloa panicea",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013361-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r2ugak
title: Occurrence Download

description: A dataset containing 274418 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Potentilla anserina",
 "Year 1957-2022"
 ]
}

 The dataset includes 274418 records from 758 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013328-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j83quu
title: Occurrence Download

description: A dataset containing 879685 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Phragmites australis",
 "Year 1957-2022"
 ]
}

 The dataset includes 879685 records from 2276 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013325-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.4742845
title: A Construction Classification System Database for Understanding Resource Use in Building Construction

description: Welcome to the Construction Classification System Database for Understanding Resource Use in Buildings. This database provides a novel dataset and a building material data structure to facilitate study of resource use in building design and construction. The ontology developed for this database uses UniFormat (CSI and CSC, 2010) in conjunction with MasterFormat (CSI and CSC, 2016) for organizing and storing the building material data. The dataset was developed by collecting design or construction drawings for the studied buildings and performing material take-offs based on the drawings. The ontology is based on Uniformat and MasterFormat to facilitate interoperability with existing construction management practices, and to suggest a standardized structure for future MI studies. The structure of the database and these guidelines builds on the structure presented by (Heeren & Fishman, 2019). The initial database version is created by the research team supervised by Prof. Shoshanna Saxe at the University of Toronto and submitted to the journal Scientific Data (Guven et al. 2021) in May 2021 to describe the dataset and the associated methods and details. Thank you for considering contributing to the database. Data contributors must follow the steps detailed below and must ensure that their inputs do not infringe any intellectual property or copyright agreements. References i. CSI and CSC. (2010). UniFormat - A Uniform Classification of Construction Systems and Assemblies. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC). ii. CSI and CSC. (2016). MasterFormat Numbers & Titles (pp. 1–186). pp. 1–186. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC). iii. Guven, G., Arceo, A., Bennett, A., Tham, M., Olanrewaju, B., McGrail, M., Isin, K., Olson, A.W., and Saxe, S. (2021). “A Construction Classification System Database for Understanding Resource Use in Building Construction”, submitted May XX, 2021 to Scientific Data, Nature. iv. Heeren, N., & Fishman, T. (2019). A database seed for a community-driven material intensity research platform. Scientific Data, 1–10. https://doi.org/10.1038/s41597-019-0021-x
DOI: 10.5281/zenodo.4762238
title: A Construction Classification System Database for Understanding Resource Use in Building Construction

description: Welcome to the Construction Classification System Database for Understanding Resource Use in Buildings. This database provides a novel dataset and a building material data structure to facilitate study of resource use in building design and construction. The ontology developed for this database uses UniFormat (CSI and CSC, 2010) in conjunction with MasterFormat (CSI and CSC, 2016) for organizing and storing the building material data. The dataset was developed by collecting design or construction drawings for the studied buildings and performing material take-offs based on the drawings. The ontology is based on Uniformat and MasterFormat to facilitate interoperability with existing construction management practices, and to suggest a standardized structure for future MI studies. The structure of the database and these guidelines builds on the structure presented by (Heeren & Fishman, 2019). The initial database version is created by the research team supervised by Prof. Shoshanna Saxe at the University of Toronto and submitted to the journal Scientific Data (Guven et al. 2021) in May 2021 to describe the dataset and the associated methods and details. Thank you for considering contributing to the database. Data contributors must follow the steps detailed below and must ensure that their inputs do not infringe any intellectual property or copyright agreements. References i. CSI and CSC. (2010). UniFormat - A Uniform Classification of Construction Systems and Assemblies. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC). ii. CSI and CSC. (2016). MasterFormat Numbers & Titles (pp. 1–186). pp. 1–186. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC). iii. Guven, G., Arceo, A., Bennett, A., Tham, M., Olanrewaju, B., McGrail, M., Isin, K., Olson, A.W., and Saxe, S. (2021). “A Construction Classification System Database for Understanding Resource Use in Building Construction”, submitted May XX, 2021 to Scientific Data, Nature. iv. Heeren, N., & Fishman, T. (2019). A database seed for a community-driven material intensity research platform. Scientific Data, 1–10. https://doi.org/10.1038/s41597-019-0021-x
DOI: 10.5281/zenodo.4775963
title: A Construction Classification System Database for Understanding Resource Use in Building Construction

description: Welcome to the Construction Classification System Database for Understanding Resource Use in Buildings. This database provides a novel dataset and a building material data structure to facilitate study of resource use in building design and construction. The ontology developed for this database uses UniFormat (CSI and CSC, 2010) in conjunction with MasterFormat (CSI and CSC, 2016) for organizing and storing the building material data. The dataset was developed by collecting design or construction drawings for the studied buildings and performing material take-offs based on the drawings. The ontology is based on Uniformat and MasterFormat to facilitate interoperability with existing construction management practices, and to suggest a standardized structure for future MI studies. The structure of the database and these guidelines builds on the structure presented by (Heeren & Fishman, 2019). The initial database version is created by the research team supervised by Prof. Shoshanna Saxe at the University of Toronto and submitted to the journal Scientific Data (Guven et al. 2021) in May 2021 to describe the dataset and the associated methods and details. Thank you for considering contributing to the database. Data contributors must follow the steps detailed below and must ensure that their inputs do not infringe any intellectual property or copyright agreements. References i. CSI and CSC. (2010). UniFormat - A Uniform Classification of Construction Systems and Assemblies. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC). ii. CSI and CSC. (2016). MasterFormat Numbers & Titles (pp. 1–186). pp. 1–186. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC). iii. Guven, G., Arceo, A., Bennett, A., Tham, M., Olanrewaju, B., McGrail, M., Isin, K., Olson, A.W., and Saxe, S. (2021). “A Construction Classification System Database for Understanding Resource Use in Building Construction”, submitted May XX, 2021 to Scientific Data, Nature. iv. Heeren, N., & Fishman, T. (2019). A database seed for a community-driven material intensity research platform. Scientific Data, 1–10. https://doi.org/10.1038/s41597-019-0021-x
DOI: 10.5281/zenodo.5576147
title: A Construction Classification System Database for Understanding Resource Use in Building Construction

description: Welcome to the Construction Classification System Database for Understanding Resource Use in Buildings. This database provides a novel dataset and a building material data structure to facilitate study of resource use in building design and construction. The ontology developed for this database uses UniFormat (CSI and CSC, 2010) in conjunction with MasterFormat (CSI and CSC, 2016) for organizing and storing the building material data. The dataset was developed by collecting design or construction drawings for the studied buildings and performing material take-offs based on the drawings. The ontology is based on Uniformat and MasterFormat to facilitate interoperability with existing construction management practices, and to suggest a standardized structure for future MI studies. The structure of the database and these guidelines builds on the structure presented by (Heeren & Fishman, 2019). The initial database version is created by the research team supervised by Prof. Shoshanna Saxe at the University of Toronto and submitted to the journal Scientific Data (Guven et al. 2021) in October 2021 to describe the dataset and the associated methods and details. Thank you for considering contributing to the database. Data contributors must follow the steps detailed below and must ensure that their inputs do not infringe any intellectual property or copyright agreements. References i. CSI and CSC. (2010). UniFormat - A Uniform Classification of Construction Systems and Assemblies. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC). ii. CSI and CSC. (2016). MasterFormat Numbers & Titles (pp. 1–186). pp. 1–186. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC). iii. Guven, G., Arceo, A., Bennett, A., Tham, M., Olanrewaju, B., McGrail, M., Isin, K., Olson, A.W., and Saxe, S. (2021). “A Construction Classification System Database for Understanding Resource Use in Building Construction”, submitted October XX, 2021 to Scientific Data, Nature. iv. Heeren, N., & Fishman, T. (2019). A database seed for a community-driven material intensity research platform. Scientific Data, 1–10. https://doi.org/10.1038/s41597-019-0021-x
DOI: 10.5281/zenodo.5586016
title: A Construction Classification System Database for Understanding Resource Use in Building Construction

description: Welcome to the Construction Classification System Database for Understanding Resource Use in Buildings. This database provides a novel dataset and a building material data structure to facilitate study of resource use in building design and construction. The ontology developed for this database uses UniFormat (CSI and CSC, 2010) in conjunction with MasterFormat (CSI and CSC, 2016) for organizing and storing the building material data. The dataset was developed by collecting design or construction drawings for the studied buildings and performing material take-offs based on the drawings. The ontology is based on Uniformat and MasterFormat to facilitate interoperability with existing construction management practices, and to suggest a standardized structure for future MI studies. The structure of the database and these guidelines builds on the structure presented by (Heeren & Fishman, 2019). The initial database version is created by the research team supervised by Prof. Shoshanna Saxe at the University of Toronto and submitted to the journal Scientific Data (Guven et al. 2021) in October 2021 to describe the dataset and the associated methods and details. Thank you for considering contributing to the database. Data contributors must follow the steps detailed below and must ensure that their inputs do not infringe any intellectual property or copyright agreements. References i. CSI and CSC. (2010). UniFormat - A Uniform Classification of Construction Systems and Assemblies. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC). ii. CSI and CSC. (2016). MasterFormat Numbers & Titles (pp. 1–186). pp. 1–186. Constructions Specification Institute (CIS) and Construction Specifications Canada (CSC). iii. Guven, G., Arceo, A., Bennett, A., Tham, M., Olanrewaju, B., McGrail, M., Isin, K., Olson, A.W., and Saxe, S. (2021). “A Construction Classification System Database for Understanding Resource Use in Building Construction”, submitted October XX, 2021 to Scientific Data, Nature. iv. Heeren, N., & Fishman, T. (2019). A database seed for a community-driven material intensity research platform. Scientific Data, 1–10. https://doi.org/10.1038/s41597-019-0021-x