{"id":"W4398979783","doi":"10.7910/dvn/xinstg/4ztdje","title":"Scores.tab","year":2018,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning; Colonoscopy; Medicine; Internal medicine","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":[0.00128744,0.004767756,0.001816311,0.005377516,0.0008868293,0.003827237,0.003433025,0.002927578,0.2216376],"category_scores_gemma":[0.007495245,0.001278209,0.002083551,0.00597931,0.000612053,0.002716109,0.002631953,0.002546437,0.2879364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001881878,"about_ca_system_score_gemma":0.001973885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01392987,"about_ca_topic_score_gemma":0.0261704,"domain_scores_codex":[0.9987974,0.0001928247,0.0001238309,0.0004198962,0.0002628866,0.0002031729],"domain_scores_gemma":[0.9976955,0.000718329,0.0001819734,0.0006351219,0.0004878606,0.0002811415],"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":[0.00006219867,0.00002714133,0.0005286706,0.000439402,0.00003343672,0.00001006708,0.00001126173,0.0002271211,0.00007343718,0.000305165,0.9957367,0.002545331],"study_design_scores_gemma":[0.0005588293,0.00004730024,0.002547816,0.0002379407,0.00004719655,0.00007197878,0.00004150006,0.001253832,0.0007406528,0.002817445,0.9915952,0.00004023015],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001706149,0.0001184076,0.0001097095,0.0001222886,0.0000455662,0.00001682501,0.9948153,0.003033451,0.001567749],"genre_scores_gemma":[0.0007530171,0.00009898106,0.0003683131,0.0001216676,0.0000209334,0.00005523645,0.9968131,0.0004755537,0.001293113],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7783624,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02148235917439666,"score_gpt":0.2736809779419699,"score_spread":0.2521986187675733,"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."}}