{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005646633,0.0002959884,0.000646889,0.0001848992,0.0001672673,0.00002752544,0.001564339,0.0002897159,0.0009474443],"category_scores_gemma":[0.0004462674,0.0002180724,0.0002248453,0.000371593,0.0006822837,0.0001113845,0.0001349854,0.0003967925,0.005409517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005122797,"about_ca_system_score_gemma":0.000364973,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1044207,"about_ca_topic_score_gemma":0.03913636,"domain_scores_codex":[0.998205,0.0001275027,0.0005315433,0.0003447067,0.0004485081,0.0003427502],"domain_scores_gemma":[0.9976861,0.000526814,0.0005563741,0.0009338832,0.00006770497,0.0002290569],"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":[0.00008613501,0.00002295512,0.004526974,0.0002836241,0.0001358923,0.00001324884,0.00007173037,0.00006703007,3.822593e-7,0.000001846444,0.994652,0.0001382233],"study_design_scores_gemma":[0.0003872119,0.0001179275,0.03242324,0.00007140753,0.000151533,0.000006905363,0.0003091605,0.00001833551,0.00001824319,0.00003464775,0.9661425,0.0003189244],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007135567,0.0007672673,0.000001206253,0.0002882094,0.0009655054,0.0002530531,0.9903111,0.00002897829,0.0002491205],"genre_scores_gemma":[0.01359404,0.0003119647,0.00001824008,0.0003981658,0.0003070149,0.000001569611,0.9852453,0.000005288636,0.0001183963],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06528433,"threshold_uncertainty_score":0.9999658,"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."}}