{"id":"W6894509434","doi":"10.5683/sp3/hoaksc","title":"iRespite Services iRépit Datasets","year":2023,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Data collection; Field (mathematics); Identification (biology); Key (lock); Service (business)","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":[0.002299882,0.003328397,0.001962791,0.004669775,0.001612716,0.003130032,0.005838826,0.002647427,0.06632239],"category_scores_gemma":[0.009726766,0.001027836,0.002097196,0.007453539,0.0007036565,0.003133008,0.004155372,0.003091731,0.1551671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001996621,"about_ca_system_score_gemma":0.00332417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02740672,"about_ca_topic_score_gemma":0.0519047,"domain_scores_codex":[0.9972542,0.0004970446,0.0002315883,0.0007971731,0.0008075786,0.0004124985],"domain_scores_gemma":[0.9969325,0.0005040414,0.0002442649,0.001092588,0.0008231566,0.0004034608],"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":[0.00004927585,0.00001842289,0.000199846,0.0002417614,0.00002018169,0.00001366608,0.00001586082,0.0001700901,0.0001427904,0.0004445964,0.9970558,0.001627759],"study_design_scores_gemma":[0.0001871657,0.00002773442,0.001983489,0.0001593165,0.00003647781,0.00009999023,0.00008373457,0.0007169595,0.0005425758,0.002020503,0.9941007,0.00004130475],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002219185,0.0001261147,0.0002645428,0.0001513359,0.00005861091,0.00003140676,0.9942357,0.002444437,0.002466008],"genre_scores_gemma":[0.0003374825,0.00004242895,0.0004944653,0.00007511612,0.000009862839,0.0000714658,0.9981077,0.0002190318,0.0006424612],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06632239,"threshold_uncertainty_score":0.2218705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02364066099468805,"score_gpt":0.301415083396097,"score_spread":0.277774422401409,"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."}}