{"id":"W6920826769","doi":"10.6084/m9.figshare.20521152","title":"Additional file 1 of Battle of the axes: simulation-based assessment of fine needle aspiration biopsies for thyroid nodules","year":2022,"lang":"en","type":"article","venue":"Open MIND","topic":"Thyroid Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Thyroid nodules; Fine-needle aspiration; Thyroid; Biopsy; Pulmonary aspiration; Nodule (geology)","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":[0.002162354,0.0008663347,0.0007839507,0.001537498,0.0007559176,0.001190379,0.001216492,0.001059838,0.8153909],"category_scores_gemma":[0.0623468,0.0004390876,0.0008368567,0.001734859,0.0002191176,0.001299937,0.0009091941,0.0009095542,0.09296991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001104901,"about_ca_system_score_gemma":0.001838205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009222105,"about_ca_topic_score_gemma":0.01441543,"domain_scores_codex":[0.9990464,0.000301864,0.0002184129,0.0001403564,0.0002082562,0.00008470826],"domain_scores_gemma":[0.9556921,0.03631239,0.002104245,0.001292062,0.003996321,0.0006029612],"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":[0.000764091,0.000276038,0.004960169,0.002334913,0.00004847513,0.00006124856,0.0001213051,0.0007541627,0.00004038754,0.0007569155,0.9695624,0.02031983],"study_design_scores_gemma":[0.02161837,0.001324244,0.1111242,0.01197119,0.0005548417,0.001110465,0.001948515,0.009753904,0.001610673,0.02582245,0.8127934,0.0003677609],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008139217,0.00002798847,0.0005756913,0.0002799711,0.0000376342,0.0005071759,0.9948455,0.0003262772,0.002585889],"genre_scores_gemma":[0.0659696,0.0004071331,0.01243511,0.001327892,0.0002886944,0.02136422,0.870072,0.001361281,0.02677404],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8153909,"threshold_uncertainty_score":0.2633225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04121269224525666,"score_gpt":0.3334397326520849,"score_spread":0.2922270404068283,"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."}}