{"id":"W3213142517","doi":"10.5281/zenodo.4575460","title":"CINECA Cohort Level metadata Representation D3.1","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"European Commission","keywords":"Metadata; Representation (politics); Computer science; Cohort; Information retrieval; World Wide Web; Statistics; Mathematics; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007599365,0.0007614691,0.0007769419,0.005781208,0.001491431,0.006921958,0.00226577,0.00147589,0.04367036],"category_scores_gemma":[0.01847639,0.0008178229,0.001637573,0.005475851,0.000787101,0.005514436,0.004609321,0.00195713,0.02130745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00418377,"about_ca_system_score_gemma":0.009612716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05724692,"about_ca_topic_score_gemma":0.04928143,"domain_scores_codex":[0.9967864,0.0005934534,0.0007703926,0.0006943664,0.000901087,0.0002544819],"domain_scores_gemma":[0.9889433,0.002187942,0.0005931135,0.004071699,0.003699014,0.0005049452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005467169,0.0001346809,0.01065814,0.001335098,0.0001314346,0.0003467573,0.001866113,0.00336603,0.005905215,0.1871166,0.6553265,0.1332667],"study_design_scores_gemma":[0.00003492363,0.00002176645,0.002489617,0.0002364328,0.00003320779,0.0001619752,0.0003594386,0.003256634,0.00290104,0.0185979,0.9718482,0.00005878517],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00621828,0.000455677,0.2751539,0.003369133,0.0009476863,0.001578011,0.6022989,0.03649243,0.07348605],"genre_scores_gemma":[0.03869545,0.0007276963,0.2415674,0.001512912,0.0002377637,0.001931928,0.680291,0.006055698,0.02898022],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05724692,"threshold_uncertainty_score":0.1460919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.104624864795498,"score_gpt":0.2778943457222909,"score_spread":0.1732694809267929,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}