{"id":"W6925283013","doi":"10.17870/bathspa.11561718.v1","title":"bête gabriel-rufael - RESEARCH TIMELINE & QUESTIONS - Matthew Sergeant","year":2021,"lang":"en","type":"dataset","venue":"Figshare","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Timeline; Performative utterance; Materiality (auditing); Percussion; Sound (geography); Chorus","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002614082,0.00126512,0.001131671,0.0039862,0.001171949,0.004161323,0.001893336,0.002533797,0.4142297],"category_scores_gemma":[0.03201558,0.0005643979,0.001146998,0.006308362,0.0005433371,0.002438586,0.003470768,0.001480391,0.3421694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001836196,"about_ca_system_score_gemma":0.002630489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02253816,"about_ca_topic_score_gemma":0.05143004,"domain_scores_codex":[0.9981692,0.0004848437,0.0001823817,0.000509213,0.000426068,0.0002281739],"domain_scores_gemma":[0.9863908,0.007405134,0.00114418,0.001609336,0.002480061,0.0009705791],"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":[0.00002312677,0.000002999192,0.0003863255,0.0003167944,0.000005038254,0.000006973875,0.00002780177,0.0000250723,0.00001457981,0.0003349676,0.9972602,0.00159593],"study_design_scores_gemma":[0.00007527304,0.000005889569,0.001711363,0.0004172185,0.000007978357,0.00002404524,0.0001003389,0.00004465488,0.0000561267,0.0007231034,0.99682,0.00001403588],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007233569,0.0001605098,0.00008870941,0.0006108895,0.0000673446,0.00002284854,0.9947954,0.0002387136,0.003943323],"genre_scores_gemma":[0.001035312,0.0002728307,0.0007752403,0.0008101037,0.00008861885,0.000471313,0.9875595,0.0004885031,0.008498506],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4142297,"threshold_uncertainty_score":0.8355303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1834465154487424,"score_gpt":0.4233097460881575,"score_spread":0.239863230639415,"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."}}