{"id":"W6958312501","doi":"10.6084/m9.figshare.14053722.v1","title":"Additional file 1 of CONECT-6: a case-finding tool to identify patients with complex health needs","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"","keywords":"Health care; MEDLINE; Data collection; Identification (biology); Key (lock); Health data","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002391151,0.0009157922,0.001006236,0.003311129,0.0009100135,0.001586854,0.0014898,0.001311888,0.8542166],"category_scores_gemma":[0.0522201,0.0005081763,0.0009134716,0.003538962,0.0002704588,0.002117436,0.001513088,0.0009522508,0.1360458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001405902,"about_ca_system_score_gemma":0.002384077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007171835,"about_ca_topic_score_gemma":0.01306001,"domain_scores_codex":[0.9987918,0.0003694731,0.0003237082,0.0001512797,0.0002322005,0.0001316397],"domain_scores_gemma":[0.9529343,0.03905226,0.002457849,0.001011203,0.003662907,0.0008815553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000269812,0.00009537869,0.002809076,0.002240552,0.00001876222,0.00006362722,0.0001353072,0.0001798573,0.00002359379,0.000672313,0.9786158,0.01487602],"study_design_scores_gemma":[0.005344904,0.0002788464,0.03572926,0.00877657,0.0001876886,0.001051261,0.001634873,0.001591454,0.000616306,0.01556899,0.9290209,0.0001989408],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0007605449,0.00009071791,0.0007757994,0.0006257739,0.00006683234,0.0009261487,0.9889803,0.0005839876,0.007190007],"genre_scores_gemma":[0.03439397,0.0009286719,0.01721129,0.002930465,0.0004439867,0.01742319,0.8823473,0.002060949,0.04226023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8542166,"threshold_uncertainty_score":0.2079423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.087919220003383,"score_gpt":0.3439738964530916,"score_spread":0.2560546764497086,"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."}}