{"id":"W2015043415","doi":"10.12968/sece.2014.2.2037","title":"How we achieved our best ever science results","year":2014,"lang":"en","type":"article","venue":"SecEd","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Mathematics education; Best practice; Science education; Psychology; Medical education; Computer science; Medicine; Political science","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":[0.0279156,0.001461951,0.0008282689,0.002334943,0.0124405,0.02931221,0.002187955,0.008401215,0.02785884],"category_scores_gemma":[0.04826825,0.0006980171,0.001369415,0.00131594,0.0124509,0.02310453,0.01356204,0.02212737,0.0225106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005788026,"about_ca_system_score_gemma":0.01420837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005460349,"about_ca_topic_score_gemma":0.007480995,"domain_scores_codex":[0.9766628,0.007275674,0.0007095962,0.00173794,0.009182171,0.004431861],"domain_scores_gemma":[0.9603699,0.005659471,0.001055296,0.00349085,0.01347824,0.01594629],"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":[0.00007998162,0.0001842466,0.002046058,0.0002865659,0.000106625,0.0003637318,0.004104034,0.0003568735,0.001084736,0.1907341,0.7253023,0.07535072],"study_design_scores_gemma":[0.00001276069,0.000047408,0.0003774164,0.0002274629,0.00001828606,0.0002253895,0.002981524,0.0001057355,0.001228162,0.05433615,0.9403981,0.00004156864],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.006361912,0.01413824,0.01762556,0.7338681,0.03212853,0.00008786148,0.0003265122,0.001628406,0.1938348],"genre_scores_gemma":[0.2074042,0.02230506,0.06327371,0.3803498,0.009950789,0.0003586271,0.0009576437,0.004070803,0.3113295],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02931221,"threshold_uncertainty_score":0.1476336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02104970694826332,"score_gpt":0.2905965758055831,"score_spread":0.2695468688573198,"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."}}