{"id":"W1970594837","doi":"10.3821/1913-701x(2008)140[s2:mtmoeo]2.0.co;2","title":"Making the most of every opportunity*","year":2007,"lang":"en","type":"article","venue":"Canadian Pharmacists Journal / Revue des Pharmaciens du Canada","topic":"Dental Education, Practice, Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science","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":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006115885,0.0002805887,0.0003213149,0.0005494999,0.003156649,0.00007096201,0.001092914,0.0001001252,0.005802189],"category_scores_gemma":[0.001948872,0.0002460546,0.0001091846,0.001229059,0.0003354651,0.0005290727,0.0001086805,0.002267858,0.00005743722],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.005148091,"about_ca_system_score_gemma":0.02827459,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1032434,"about_ca_topic_score_gemma":0.2304288,"domain_scores_codex":[0.9953347,0.0007291117,0.001109941,0.0002934092,0.0008621244,0.00167074],"domain_scores_gemma":[0.9937816,0.000900724,0.0007213653,0.0004205066,0.00143608,0.002739767],"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":[0.0006524739,0.0002064704,0.2089224,0.001229492,0.0006083706,0.05734286,0.01998186,0.000244657,0.004453403,0.0008232648,0.3891235,0.3164113],"study_design_scores_gemma":[0.001810187,0.00005041196,0.005070913,0.0001201867,0.0002117805,0.1833526,0.002109363,0.0006314568,0.001291943,0.0002692918,0.8043434,0.0007385187],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551991,0.001438625,0.0001348298,0.001107707,0.006926138,0.0009249902,0.0003654314,0.00002512215,0.03387801],"genre_scores_gemma":[0.9828683,0.001689665,0.00006905821,0.009314938,0.001478944,0.00002019935,0.00002346576,0.00006286381,0.004472617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4152199,"threshold_uncertainty_score":0.9999992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2148203235567819,"score_gpt":0.4873058027963837,"score_spread":0.2724854792396019,"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."}}