{"id":"W4231504173","doi":"10.31234/osf.io/y8xcf","title":"Mixed-effects design analysis for experimental phonetics","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Statistical power; Sample size determination; Sign (mathematics); Phonetics; Null hypothesis; Magnitude (astronomy); Type I and type II errors; Statistics; Value (mathematics); Econometrics; Null (SQL); Sample (material); Computer science; Mathematics; Psychology; Linguistics; Data mining","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":[0.1401188,0.006191555,0.007255638,0.006220514,0.004327526,0.007509043,0.007784509,0.007131489,0.08632675],"category_scores_gemma":[0.3914226,0.003103607,0.01186212,0.00862879,0.00566739,0.00605188,0.006529158,0.01311818,0.01440567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00625849,"about_ca_system_score_gemma":0.007999478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00211379,"about_ca_topic_score_gemma":0.002692914,"domain_scores_codex":[0.7458013,0.1959043,0.01062955,0.01739528,0.02752488,0.002744709],"domain_scores_gemma":[0.6357331,0.278502,0.01852,0.05226304,0.01369986,0.001281928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.004849212,0.001671183,0.004826927,0.01857184,0.00674079,0.001155621,0.007386172,0.01015113,0.007712399,0.4290391,0.1919894,0.3159062],"study_design_scores_gemma":[0.004350271,0.009629115,0.008734814,0.00665162,0.003189714,0.0007851496,0.001710586,0.07417198,0.01396256,0.3455263,0.5302053,0.001082571],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002436882,0.0006872361,0.9612757,0.00112672,0.003180004,0.01488215,0.004875139,0.006025042,0.00551117],"genre_scores_gemma":[0.00854916,0.000238758,0.910336,0.0007572243,0.0002411026,0.07643486,0.0006176287,0.001126446,0.001698843],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1401188,"threshold_uncertainty_score":0.7410277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09505999670829285,"score_gpt":0.3023379607484315,"score_spread":0.2072779640401387,"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."}}