{"id":"W4388863266","doi":"10.1075/jslp.23029.mun","title":"Listening to the “noise” in the data","year":2023,"lang":"en","type":"article","venue":"Journal of Second Language Pronunciation","topic":"Educational Assessment and Pedagogy","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Active listening; Noise (video); Phenomenon; Variation (astronomy); Process (computing); Term (time); Computer science; Psychology; Data science; Cognitive psychology; Epistemology; Artificial intelligence; Communication; Philosophy; Physics","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":[0.1012346,0.001188054,0.001708605,0.002930523,0.003077325,0.01031257,0.00214693,0.005619901,0.005520475],"category_scores_gemma":[0.4717658,0.000902144,0.0008255237,0.002466952,0.009687571,0.01023505,0.005599438,0.01009634,0.002701371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002013332,"about_ca_system_score_gemma":0.00192339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000777018,"about_ca_topic_score_gemma":0.0005623852,"domain_scores_codex":[0.8452147,0.1232045,0.00663864,0.006798281,0.01696691,0.001177002],"domain_scores_gemma":[0.4131222,0.5250782,0.01472952,0.02634598,0.01866272,0.002061413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.002289357,0.0002941479,0.04103319,0.005502341,0.0009981442,0.003820571,0.3721626,0.004631143,0.04539906,0.1116248,0.1064672,0.3057773],"study_design_scores_gemma":[0.0002292867,0.0009191002,0.04171383,0.007195822,0.0005769921,0.005033541,0.1300662,0.02411788,0.02983069,0.3953844,0.3638582,0.001074224],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.156686,0.004548838,0.6550484,0.139201,0.009410026,0.001065707,0.002041993,0.002511263,0.02948668],"genre_scores_gemma":[0.8134813,0.00224001,0.1300948,0.03839467,0.004220472,0.001866108,0.001113454,0.001529024,0.007060364],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1012346,"threshold_uncertainty_score":0.535386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08183322280436586,"score_gpt":0.4255216674573442,"score_spread":0.3436884446529783,"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."}}