{"id":"W7128647520","doi":"10.7910/dvn/sjffb2","title":"Sub-evaluation 1 UBC Dataset","year":2025,"lang":"","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Segmentation; Feature (linguistics); Medical imaging; Image segmentation","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":[0.003067089,0.005683961,0.002667902,0.006763498,0.002727451,0.003683754,0.006043468,0.004332146,0.0462436],"category_scores_gemma":[0.01166749,0.0006740688,0.002447027,0.007069805,0.001236721,0.002805047,0.003659646,0.003027364,0.07549475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004347675,"about_ca_system_score_gemma":0.004780771,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05586861,"about_ca_topic_score_gemma":0.1033687,"domain_scores_codex":[0.994786,0.001098779,0.0005234682,0.001388084,0.00153512,0.0006684682],"domain_scores_gemma":[0.9943551,0.001234248,0.0002836844,0.001479479,0.002092564,0.0005550497],"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":[0.0001760905,0.0001311973,0.0006125987,0.0006403421,0.00006381078,0.00003677547,0.00001988058,0.0005668665,0.0002223582,0.0003755957,0.9896386,0.007515845],"study_design_scores_gemma":[0.001185923,0.0002800675,0.009077366,0.000902738,0.0001897547,0.000621683,0.0003204712,0.01058809,0.002563858,0.00397145,0.9701389,0.0001597552],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00263631,0.001107095,0.0005932372,0.0004152961,0.0003270361,0.0002390665,0.9871752,0.003281966,0.004224812],"genre_scores_gemma":[0.001159122,0.0001002485,0.00101611,0.0001183296,0.00002981118,0.0001686444,0.9959612,0.0001575544,0.001289092],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9441314,"threshold_uncertainty_score":0.1547003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1104281023012383,"score_gpt":0.4197240333804776,"score_spread":0.3092959310792393,"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."}}