{"id":"W4398393517","doi":"10.7910/dvn/fmk6sq/peglep","title":"32.tif","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Head and Neck Cancer Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Methylene blue; Staining; Degree (music); Lymph; Pathology; Chemistry; Computer science; Medicine; Physics; Acoustics; Biochemistry","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":[0.001811952,0.002528037,0.001985064,0.004978813,0.0007499261,0.004780578,0.003075548,0.002602621,0.4096098],"category_scores_gemma":[0.01256594,0.0009890684,0.002446949,0.008041278,0.0005824433,0.002184905,0.002776402,0.002094063,0.3861196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001685909,"about_ca_system_score_gemma":0.002564841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02154134,"about_ca_topic_score_gemma":0.03512402,"domain_scores_codex":[0.998848,0.0002650749,0.0001386784,0.0003157292,0.000187017,0.0002454333],"domain_scores_gemma":[0.996904,0.001123163,0.0002651255,0.0007060183,0.0006105544,0.000391101],"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":[0.0000444157,0.000006700417,0.0002310864,0.0005970593,0.00002845015,0.000006811621,0.000009608766,0.00008483747,0.00002325802,0.000215534,0.9976822,0.001069954],"study_design_scores_gemma":[0.0007263619,0.00002726732,0.002049351,0.0007338849,0.0000515931,0.00003645406,0.00005192143,0.0002892255,0.0001314816,0.001865377,0.9940053,0.0000318779],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002745858,0.00006107163,0.00002396218,0.00008696668,0.000040355,0.000005397137,0.9986216,0.0003668917,0.0007663596],"genre_scores_gemma":[0.0004146826,0.000115069,0.0001705429,0.0001790219,0.00002824171,0.00007429318,0.9971067,0.0003475141,0.001563896],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5903902,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03136751662768513,"score_gpt":0.2894953516189448,"score_spread":0.2581278349912597,"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."}}