{"id":"W2020285027","doi":"10.1016/j.aodf.2009.10.005","title":"Aesthetic and Biomechanical Precision in Complex Cases","year":2009,"lang":"en","type":"article","venue":"Alpha Omegan","topic":"Dental materials and restorations","field":"Dentistry","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Term (time); Precision medicine; Accuracy and precision; Computer science; Orthodontics; Dentistry; Medicine; Mathematics; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000792527,0.00007071312,0.000112602,0.00007043147,0.000050932,0.00007117195,0.00006773208,0.00005127627,0.0001461006],"category_scores_gemma":[0.00002190258,0.00005953071,0.00001932139,0.0001127085,0.00002596891,0.00008416043,0.00002799216,0.00004150064,0.0001551649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001531671,"about_ca_system_score_gemma":0.000005797435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007138793,"about_ca_topic_score_gemma":0.0001754006,"domain_scores_codex":[0.9994377,0.00003578364,0.0001628344,0.0001456719,0.0000987851,0.000119215],"domain_scores_gemma":[0.9997627,0.00001665979,0.0000283644,0.0001280406,0.0000104518,0.00005375778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001965049,0.0009387863,0.004594978,0.00002659715,0.000007955225,0.002332677,0.0003088126,0.000006700261,0.8295376,0.01948204,0.01032582,0.1322415],"study_design_scores_gemma":[0.002836879,0.001009323,0.9060111,0.0001162732,0.00002406612,0.00457145,0.000235095,0.0006761481,0.01735047,0.01617577,0.05038452,0.0006088759],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985107,0.0001447035,0.00002637647,0.0003199238,0.000172797,0.0001017923,0.00001128011,0.00003169271,0.0006807792],"genre_scores_gemma":[0.9993289,0.00002301302,0.0001577102,0.0001431508,0.00003464522,0.000002800311,0.0000208294,0.000005879237,0.0002830369],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9014161,"threshold_uncertainty_score":0.2427592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0335753461976413,"score_gpt":0.3101386070183879,"score_spread":0.2765632608207466,"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."}}