{"id":"W2178824826","doi":"10.1177/0145445515613584","title":"Using Single-Case Experiments to Support Evidence-Based Decisions","year":2015,"lang":"en","type":"article","venue":"Behavior Modification","topic":"Behavioral and Psychological Studies","field":"Psychology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Intervention (counseling); Outcome (game theory); Psychological intervention; Psychology; Management science; Set (abstract data type); Risk analysis (engineering); Computer science; Applied psychology; Medicine; Engineering; Microeconomics; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"opus","categories":["metaresearch"],"domain":"methods","study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003540907,0.0002018359,0.0002039953,0.0001302176,0.0001755752,0.00005483526,0.0002240777,0.0001552905,0.000750078],"category_scores_gemma":[0.0001208693,0.0001744155,0.00008544489,0.0003711046,0.00007209466,0.0001510558,0.00005442731,0.0001182259,0.001076984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001776625,"about_ca_system_score_gemma":0.00003173721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003727481,"about_ca_topic_score_gemma":0.00001245317,"domain_scores_codex":[0.9982318,0.0001480255,0.0004078425,0.0005539205,0.0003135281,0.0003449297],"domain_scores_gemma":[0.9986067,0.00008456887,0.0001192462,0.0006048246,0.0002180676,0.0003665536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001037411,0.009736135,0.1467696,0.000005066467,0.00003940292,0.002467045,0.008367161,0.0001539792,0.2100944,0.001198104,0.02410768,0.596024],"study_design_scores_gemma":[0.007802851,0.0085675,0.8910672,0.0003813402,0.001327472,0.002617553,0.01344709,0.0002472677,0.03085531,0.0004857008,0.03971172,0.003488968],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987772,0.0002441405,0.008818395,0.0002985253,0.001027831,0.0007158733,0.00002420264,0.0001368987,0.0009620759],"genre_scores_gemma":[0.9923477,0.000001355868,0.006039409,0.0003765863,0.00009797759,0.0005747302,0.00002051114,0.00002382117,0.0005179537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7442977,"threshold_uncertainty_score":0.9997008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9424849945236604,"score_gpt":0.5344856442156805,"score_spread":0.40799935030798,"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."}}