{"id":"W6906735677","doi":"10.17632/4dv53x925y.2","title":"Third molar size predictive model (and associated dataset)","year":2021,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Dental Radiography and Imaging","field":"Dentistry","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":[0.001752971,0.001930373,0.00108255,0.002177192,0.001067944,0.001481964,0.004257525,0.002021849,0.02980475],"category_scores_gemma":[0.006825047,0.0005311146,0.001818175,0.003491925,0.000596803,0.0005479661,0.001042768,0.00237071,0.01808214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004826297,"about_ca_system_score_gemma":0.007042973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4643379,"about_ca_topic_score_gemma":0.5163584,"domain_scores_codex":[0.9991676,0.0001287057,0.00005280206,0.0002723439,0.00020428,0.0001744037],"domain_scores_gemma":[0.9975383,0.0009581107,0.000121985,0.0003919119,0.0008412287,0.0001484078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007002556,0.0004895261,0.02646699,0.001065383,0.0003245952,0.0002769386,0.00008588973,0.01943097,0.0004747733,0.001286795,0.9210004,0.02839752],"study_design_scores_gemma":[0.001776518,0.0003430166,0.1221765,0.0009010154,0.0007396023,0.0008041187,0.0005607266,0.08394349,0.00231869,0.004647642,0.7815213,0.000267505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007569761,0.0003411463,0.0007914425,0.0002966435,0.0000632864,0.0001009545,0.988903,0.0007133139,0.001220471],"genre_scores_gemma":[0.0104169,0.0001255348,0.001300103,0.00006683299,0.00001336136,0.0001824531,0.9867835,0.00004600506,0.001065411],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4643379,"threshold_uncertainty_score":0.9232703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01420149517417856,"score_gpt":0.2605558361128629,"score_spread":0.2463543409386843,"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."}}