{"id":"W2913423479","doi":"10.1002/ajpa.23797","title":"Technical note: Comparing dental topography software using platyrrhine molars","year":2019,"lang":"en","type":"article","venue":"American Journal of Physical Anthropology","topic":"Orthodontics and Dentofacial Orthopedics","field":"Dentistry","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"National Science Foundation","keywords":"Software; Consistency (knowledge bases); Molar; Orientation (vector space); Mathematics; Statistics; Computer science; Algorithm; Geometry; Orthodontics; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.02612681,0.0007428274,0.0005035537,0.00379336,0.001177137,0.002925683,0.001849176,0.0006498391,0.008857987],"category_scores_gemma":[0.08936834,0.000571961,0.001167338,0.004205805,0.001421385,0.00205021,0.003447274,0.000845761,0.002378971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008447253,"about_ca_system_score_gemma":0.001808809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004237643,"about_ca_topic_score_gemma":0.01192729,"domain_scores_codex":[0.9834964,0.005009279,0.002286849,0.002272294,0.006678071,0.0002570747],"domain_scores_gemma":[0.9438981,0.02350223,0.005946503,0.009125377,0.01679914,0.0007286099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007480026,0.0001819596,0.3610875,0.002022159,0.0005285812,0.0006140784,0.01239876,0.003739014,0.0395236,0.009956881,0.02852504,0.5406744],"study_design_scores_gemma":[0.0001393396,0.0009549411,0.7544042,0.000922264,0.0004455734,0.002436353,0.00616828,0.0199829,0.05883668,0.01175882,0.143605,0.0003456459],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5346279,0.0008192546,0.4134308,0.002595273,0.001095861,0.001431707,0.009386764,0.006884343,0.02972816],"genre_scores_gemma":[0.457976,0.0003840463,0.5264375,0.0004043347,0.0001773136,0.002289576,0.004223113,0.003187197,0.004920948],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02612681,"threshold_uncertainty_score":0.1381735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01475144087396168,"score_gpt":0.3278576261297553,"score_spread":0.3131061852557936,"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."}}