{"id":"W1491759212","doi":"","title":"INVESTIGATING SOUND INTENSITY GRADIENTS AS FEEDBACK FOR EMBODIED LEARNING","year":2007,"lang":"en","type":"article","venue":"Summit (Simon Fraser University)","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Embodied cognition; Computer science; Context (archaeology); Human–computer interaction; Audio feedback; Modal; Sound (geography); Artificial intelligence; Acoustics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003877493,0.0001737065,0.0002255221,0.000330708,0.0008376213,0.00005166963,0.0007701552,0.000164388,0.000006755264],"category_scores_gemma":[0.0002666221,0.0001938377,0.0001043312,0.0007116317,0.0002420103,0.0003825203,0.0004609732,0.0003389076,0.00004395592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001142773,"about_ca_system_score_gemma":0.00003909839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007939797,"about_ca_topic_score_gemma":0.005988503,"domain_scores_codex":[0.9987325,0.00003576066,0.0001553589,0.0004552711,0.0001570157,0.00046411],"domain_scores_gemma":[0.9990365,0.0002052794,0.0001221362,0.0003263911,0.0001826976,0.0001269908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004572411,0.00005313598,0.7669784,0.00002379086,0.0001021805,0.0000919791,0.0005261881,0.00005250265,0.00001076064,0.2198535,0.005767039,0.006494734],"study_design_scores_gemma":[0.005925574,0.001061805,0.03363547,0.0001666287,0.0001713976,2.601463e-7,0.0868292,0.008169131,0.0039523,0.2122515,0.64582,0.002016727],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8064035,0.00004729118,0.1729445,0.0004345146,0.0004393056,0.0002035564,0.00000168149,0.0004738793,0.01905177],"genre_scores_gemma":[0.9891882,0.000008248575,0.007550715,0.0003573005,0.000042952,5.965168e-7,0.000004647383,0.000008299507,0.00283903],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7333429,"threshold_uncertainty_score":0.7904471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02224264127799761,"score_gpt":0.2298409072081518,"score_spread":0.2075982659301542,"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."}}