{"id":"W4398680060","doi":"10.7910/dvn/fmk6sq/e80xvo","title":"55.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; Degree (music); Staining; Lymph; Computer science; Pathology; Chemistry; Medicine; Physics; Biochemistry; Acoustics","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":[0.001930991,0.003306688,0.002325787,0.005821196,0.0009974493,0.00563061,0.003427848,0.002880348,0.5258089],"category_scores_gemma":[0.01313713,0.001115723,0.002547964,0.008524536,0.0007396829,0.002319057,0.003181721,0.002337539,0.5540832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001902642,"about_ca_system_score_gemma":0.003020213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02578474,"about_ca_topic_score_gemma":0.03831118,"domain_scores_codex":[0.9986982,0.0002674067,0.0001415749,0.0003895474,0.0002230079,0.0002802556],"domain_scores_gemma":[0.996435,0.001218019,0.0002902634,0.0008204888,0.000745216,0.0004908555],"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":[0.00003359444,0.000007222316,0.0001787642,0.0004186475,0.00002036826,0.000004901458,0.000008605462,0.0000728118,0.00002449407,0.0001698334,0.998168,0.0008928319],"study_design_scores_gemma":[0.0007352612,0.0000275297,0.001985693,0.0007133896,0.00004893633,0.00003375385,0.00005854063,0.000286538,0.0001517473,0.001568603,0.9943523,0.00003760862],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002221699,0.0000460963,0.00002093043,0.00007015753,0.00004189829,0.000005011038,0.9986197,0.0003859973,0.0007879509],"genre_scores_gemma":[0.0002755777,0.00009580857,0.0001408535,0.0001653876,0.00002406013,0.00006255805,0.99705,0.0003521743,0.001833544],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4741911,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03147191538410277,"score_gpt":0.2896872495929347,"score_spread":0.2582153342088319,"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."}}