{"id":"W4251427753","doi":"10.1075/sibil.57.02bia","title":"The signal and the noise","year":2019,"lang":"en","type":"book-chapter","venue":"Studies in bilingualism","topic":"Neuroscience and Music Perception","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Noise (video); SIGNAL (programming language); Computer science; Acoustics; Physics; Artificial intelligence","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":[0.002430742,0.000481658,0.0006662555,0.001266174,0.0006831312,0.00488919,0.0008859551,0.001887402,0.01807924],"category_scores_gemma":[0.01302099,0.0003764039,0.0003393511,0.0009344402,0.004474064,0.003930978,0.001888015,0.002768585,0.007529389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008534412,"about_ca_system_score_gemma":0.0006516106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006821326,"about_ca_topic_score_gemma":0.000833282,"domain_scores_codex":[0.9982033,0.0005358373,0.00008532092,0.0004209656,0.0006789315,0.0000755619],"domain_scores_gemma":[0.9932202,0.005141855,0.0001958787,0.000722644,0.0005393263,0.000180104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003974106,0.00004561636,0.002805817,0.0005782576,0.00009935093,0.0007338269,0.0008478641,0.001458043,0.01618804,0.611342,0.04612195,0.3193819],"study_design_scores_gemma":[0.00004363016,0.0001704299,0.005298603,0.0005140755,0.0000805653,0.001886049,0.0004675992,0.009099565,0.01285437,0.7302679,0.2392268,0.00009044631],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03623004,0.03238724,0.4918944,0.04964805,0.008702915,0.00008560074,0.001279808,0.002142465,0.3776295],"genre_scores_gemma":[0.6215529,0.01793825,0.1247987,0.01847984,0.008624454,0.0002253819,0.0008664119,0.001740646,0.2057734],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01807924,"threshold_uncertainty_score":0.06048113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09084478671308735,"score_gpt":0.3432855115384132,"score_spread":0.2524407248253259,"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."}}