{"id":"W4226366257","doi":"10.3758/s13428-022-01858-9","title":"Waiting for baseline stability in single-case designs: Is it worth the time and effort?","year":2022,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Behavioral and Psychological Studies","field":"Psychology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut universitaire en santé mentale de Montréal; Université de Montréal; Institut Universitaire en Santé Mentale de Québec","funders":"","keywords":"Baseline (sea); Computer science; Classifier (UML); Stability (learning theory); Machine learning; Support vector machine; Multiple baseline design; Monte Carlo method; Artificial intelligence; Graph; Statistics; Mathematics; Psychology; Theoretical computer 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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.6163899,0.002023129,0.006311454,0.003059454,0.003175913,0.006176334,0.007415993,0.00793362,0.005710357],"category_scores_gemma":[0.8366914,0.002100063,0.00668268,0.005519268,0.01037558,0.01581182,0.002935665,0.009835789,0.001766129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006081562,"about_ca_system_score_gemma":0.01325904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002837376,"about_ca_topic_score_gemma":0.005312429,"domain_scores_codex":[0.4278531,0.4761989,0.04265254,0.01772043,0.03387453,0.001700498],"domain_scores_gemma":[0.09419916,0.7471616,0.05792997,0.06640577,0.03139611,0.002907277],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01169612,0.00149635,0.0268872,0.01281971,0.006681227,0.0007335747,0.0118975,0.009637808,0.003891202,0.1290101,0.06099158,0.7242576],"study_design_scores_gemma":[0.01163324,0.02002444,0.04617759,0.02754595,0.005688784,0.001983184,0.00406708,0.05765428,0.01451152,0.6712124,0.1373818,0.002119761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0351854,0.01572693,0.8432415,0.07709104,0.01228367,0.008835361,0.0005686887,0.001952864,0.005114566],"genre_scores_gemma":[0.2437931,0.002994397,0.7009397,0.02550376,0.004033473,0.02047052,0.0003473566,0.0005308707,0.001386781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3836101,"threshold_uncertainty_score":0.4730595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.872368813169848,"score_gpt":0.6139927190547214,"score_spread":0.2583760941151266,"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."}}