{"id":"W4398272567","doi":"10.7910/dvn/fmk6sq/ax4zle","title":"648179_1.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; 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":[0.001257225,0.002062087,0.001968987,0.004073882,0.00063681,0.003051876,0.003154943,0.00218923,0.2652552],"category_scores_gemma":[0.01011884,0.000941381,0.001595771,0.007334004,0.000428594,0.001468653,0.002474399,0.001409487,0.2301051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001536629,"about_ca_system_score_gemma":0.002127207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02047843,"about_ca_topic_score_gemma":0.0298003,"domain_scores_codex":[0.9989606,0.0002581115,0.0001195941,0.0003214355,0.0001690722,0.0001711918],"domain_scores_gemma":[0.9972149,0.001090488,0.0003709058,0.0004997528,0.0004731557,0.0003507448],"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":[0.00006259108,0.000008153594,0.0004673491,0.0007124966,0.0000408319,0.000007812734,0.00001032417,0.0001596392,0.00002904597,0.0003630396,0.9963282,0.00181058],"study_design_scores_gemma":[0.0006025031,0.00002881989,0.002803614,0.0006427006,0.0000730484,0.00004919945,0.00003559202,0.0003369375,0.0001701881,0.001813449,0.9934186,0.00002534648],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004434831,0.0001004818,0.00003067584,0.00006895329,0.00001661177,0.000004801819,0.9987397,0.0002457366,0.0007487097],"genre_scores_gemma":[0.0005381771,0.0001555309,0.0002053378,0.0001496191,0.00002228832,0.0000770378,0.9972505,0.0002067468,0.001394802],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7347448,"threshold_uncertainty_score":0.887367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03126847295093408,"score_gpt":0.2894427915943308,"score_spread":0.2581743186433967,"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."}}