{"id":"W6906714799","doi":"10.17632/4dv53x925y","title":"Third molar size predictive model (and associated dataset)","year":2021,"lang":"en","type":"dataset","venue":"Mendeley Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Crown (dentistry); Molar; Computed tomography; Mandibular second molar","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001646239,0.002182383,0.001235838,0.00219585,0.001025326,0.001535253,0.004643232,0.002299735,0.04093777],"category_scores_gemma":[0.007620636,0.0005902363,0.002023482,0.00327278,0.0005648454,0.0006291383,0.001138257,0.002306387,0.02396045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004131591,"about_ca_system_score_gemma":0.005681873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3459795,"about_ca_topic_score_gemma":0.4138238,"domain_scores_codex":[0.9991879,0.000136181,0.00004928981,0.0002985357,0.0001779075,0.0001500914],"domain_scores_gemma":[0.9977762,0.001005803,0.0001076485,0.0003672708,0.0006141796,0.0001288846],"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":[0.0005367865,0.0002770433,0.0144735,0.001045451,0.0002956116,0.0001875539,0.00005707752,0.01725017,0.0003831216,0.001091564,0.941888,0.02251413],"study_design_scores_gemma":[0.001718276,0.00026441,0.06608193,0.0009244991,0.0006424292,0.0005522282,0.0003665782,0.07551362,0.001959772,0.004824306,0.84692,0.0002319064],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004467728,0.000372027,0.0006949824,0.0002554333,0.00005890091,0.00006847413,0.9921353,0.0008691713,0.001078055],"genre_scores_gemma":[0.007453166,0.0001087711,0.001326232,0.00006031306,0.00001181016,0.0001496649,0.9898511,0.00006610047,0.0009729039],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3459795,"threshold_uncertainty_score":0.6879314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05795167647262952,"score_gpt":0.3108741144019651,"score_spread":0.2529224379293356,"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."}}