{"id":"W6948311641","doi":"10.48580/dfsr","title":"Catalogue of Life Checklist","year":2023,"lang":"en","type":"dataset","venue":"The Catalogue of Life","topic":"Subterranean biodiversity and taxonomy","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; University of British Columbia; Agriculture and Agri-Food Canada","funders":"","keywords":"Checklist; Data collection; MEDLINE","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":[0.002336631,0.003243192,0.002243326,0.0162725,0.001527622,0.004755951,0.003736105,0.002374285,0.1859274],"category_scores_gemma":[0.01314802,0.001411215,0.001483123,0.02494165,0.0007793575,0.002851117,0.003504847,0.00340012,0.2283515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003312095,"about_ca_system_score_gemma":0.008930916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07102896,"about_ca_topic_score_gemma":0.07846472,"domain_scores_codex":[0.997525,0.0003274997,0.0004757153,0.000578994,0.000629547,0.0004633017],"domain_scores_gemma":[0.99052,0.00205571,0.001013357,0.001907591,0.003311333,0.001192005],"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":[0.00003549358,0.00001010207,0.0003755064,0.0005715124,0.00001426447,0.00001075029,0.00003431633,0.0001207351,0.0000755917,0.0009624767,0.9952609,0.002528401],"study_design_scores_gemma":[0.00005880649,0.00000602915,0.002016212,0.0002806929,0.00001450231,0.00002452808,0.00005505513,0.00008179919,0.00008227087,0.001014159,0.9963477,0.00001819256],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003578925,0.0000289393,0.00005480334,0.00001857196,0.0000140255,0.000007843716,0.9987759,0.0001302382,0.0009338775],"genre_scores_gemma":[0.0001100844,0.00004765945,0.0002782655,0.00003129094,0.000003262522,0.00004782619,0.998618,0.0000838223,0.0007798548],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1859274,"threshold_uncertainty_score":0.621989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05014408878359494,"score_gpt":0.2077300199755668,"score_spread":0.1575859311919718,"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."}}