{"id":"W1606273442","doi":"","title":"Eliciting individual language describing differences in auditory imagery associated with four multichannel microphone techniques","year":2007,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Hearing Loss and Rehabilitation","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Social Sciences and Humanities Research Council of Canada; Centre for Interdisciplinary Research in Music Media and Technology; McGill University","keywords":"Loudspeaker; Microphone; Active listening; Acoustics; Centroid; Speech recognition; Computer science; Psychology; Artificial intelligence; Communication; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0008233579,0.000456883,0.000359423,0.0004116815,0.0001515328,0.000387154,0.0002202629,0.0004280784,0.003704403],"category_scores_gemma":[0.005301236,0.0001767735,0.0002531663,0.0001691194,0.0004460204,0.0003416548,0.0009704522,0.000528882,0.0003956678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009414626,"about_ca_system_score_gemma":0.0001139502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001538177,"about_ca_topic_score_gemma":0.0005235121,"domain_scores_codex":[0.9993423,0.0002143965,0.00006030216,0.0001129256,0.0001852726,0.00008490977],"domain_scores_gemma":[0.9975069,0.001649008,0.0002092474,0.0001782279,0.0002807902,0.0001758081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0009502922,0.00008019638,0.001819378,0.0001803436,0.00001397333,0.0001202486,0.0006962728,0.0001089809,0.9771594,0.00007747043,0.00006302075,0.01873033],"study_design_scores_gemma":[0.0002316588,0.01322467,0.3157251,0.00007949023,0.0001603999,0.00266041,0.004518668,0.00429865,0.654313,0.0008458225,0.003829662,0.000112444],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908307,0.00008758235,0.006958096,0.00003816481,0.00002273966,0.00009270977,0.00005566601,0.0000410903,0.001873317],"genre_scores_gemma":[0.9813455,0.0001399623,0.01624751,0.00004372145,0.00002338751,0.0001502711,0.00009968421,0.00003401525,0.001916017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003704403,"threshold_uncertainty_score":0.01239246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0487750101431486,"score_gpt":0.2499777679550003,"score_spread":0.2012027578118518,"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."}}