{"id":"W6929368408","doi":"10.48580/dfqt","title":"Catalogue of Life Checklist","year":2022,"lang":"en","type":"dataset","venue":"The Catalogue of Life","topic":"Clusterin in disease pathology","field":"Medicine","cited_by":2,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007572134,0.0004631143,0.001516223,0.0002980565,0.0001097143,0.000008066201,0.00132878,0.0003634173,0.007322825],"category_scores_gemma":[0.002875821,0.0003673838,0.0004265957,0.0003898184,0.0009997602,0.00003888166,0.001381144,0.0009433392,0.0001498332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001159632,"about_ca_system_score_gemma":0.001344164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003413639,"about_ca_topic_score_gemma":0.0004648292,"domain_scores_codex":[0.9968266,0.0002795065,0.001156255,0.000548069,0.0007626261,0.000426923],"domain_scores_gemma":[0.9949906,0.0004648572,0.00101098,0.002969318,0.0001761847,0.000388034],"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":[0.0006578687,0.0004119325,0.0001797404,0.002171834,0.0003415548,0.0001225786,0.000143036,0.00001277572,0.0001095518,0.00001885242,0.9957954,0.00003482156],"study_design_scores_gemma":[0.001566578,0.0003912072,0.002674727,0.0001876916,0.0009371179,0.0001837685,0.000251751,0.000003492271,0.0000998169,0.00003684015,0.9933382,0.0003288035],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.008520258,0.003285467,0.000002538395,0.001177057,0.001034211,0.0007847061,0.9850214,0.00003652831,0.0001379056],"genre_scores_gemma":[0.007309576,0.0004542293,0.00002688003,0.001848795,0.0004867117,0.0001472369,0.9893961,0.00006550593,0.0002649843],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007172992,"threshold_uncertainty_score":0.9998778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02669113222876716,"score_gpt":0.2840591839130159,"score_spread":0.2573680516842488,"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."}}