{"id":"W4398621562","doi":"10.7910/dvn/fmk6sq/umc5gr","title":"648945_3.roi","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; Computer science; Biomedical engineering; Medicine; Chemistry; Physics","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":[0.001246846,0.002119517,0.001925653,0.00384638,0.0006586547,0.003080706,0.003209757,0.00227186,0.2516981],"category_scores_gemma":[0.009033887,0.0009419727,0.001665331,0.006670189,0.0004519142,0.001409717,0.002511147,0.00141775,0.2308549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001525634,"about_ca_system_score_gemma":0.002061396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02090428,"about_ca_topic_score_gemma":0.02956138,"domain_scores_codex":[0.9990044,0.0002423432,0.0001114107,0.0003147984,0.0001583114,0.0001687548],"domain_scores_gemma":[0.9975976,0.0008921702,0.0003158995,0.0004660711,0.0004177964,0.0003105286],"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":[0.0000658438,0.00000892905,0.0004871025,0.0006932262,0.00004297297,0.000008404063,0.00001087251,0.0001758268,0.00003211401,0.0003539959,0.9962962,0.001824378],"study_design_scores_gemma":[0.0006438595,0.000030073,0.002821809,0.0005933922,0.00007331127,0.00005311631,0.00003778851,0.0003788475,0.0001909116,0.001869621,0.9932808,0.00002656599],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005003214,0.0001031138,0.00003459322,0.00006882098,0.00001760566,0.00000490197,0.9986797,0.0002929723,0.0007482136],"genre_scores_gemma":[0.0005638083,0.0001419893,0.0002091559,0.0001456987,0.00002162191,0.00007327925,0.9973119,0.0002036076,0.001328922],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7483019,"threshold_uncertainty_score":0.8420141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03115466767554933,"score_gpt":0.2892119369478477,"score_spread":0.2580572692722984,"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."}}