{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009791795,0.0003405917,0.0002749801,0.0003039878,0.0004654397,0.001974354,0.0006099202,0.0005592467,0.002942718],"category_scores_gemma":[0.00535656,0.0002817339,0.0002665401,0.0002516247,0.001593497,0.002197023,0.001781943,0.0007075183,0.000216335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006141081,"about_ca_system_score_gemma":0.0002648366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004086313,"about_ca_topic_score_gemma":0.0003051272,"domain_scores_codex":[0.9994242,0.0002561465,0.00002127071,0.00009405406,0.0001455,0.00005886303],"domain_scores_gemma":[0.9973332,0.002139412,0.0001884454,0.0001063597,0.0001510474,0.00008162367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001148385,0.0005289754,0.008199461,0.00130706,0.00008267112,0.000604986,0.01828508,0.08032838,0.4134746,0.2568901,0.0007312718,0.2184192],"study_design_scores_gemma":[0.0004310592,0.002392032,0.02114462,0.0003040149,0.0002123143,0.0007619027,0.009201223,0.4159013,0.2081435,0.3174993,0.02373774,0.000270915],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6028467,0.0008202329,0.3660263,0.0006899309,0.000074908,0.0001498435,0.00003488682,0.0002919534,0.0290653],"genre_scores_gemma":[0.9779297,0.0001718434,0.02038097,0.00003013204,0.000009367772,0.00004959972,0.000006997426,0.00002635744,0.001395139],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002942718,"threshold_uncertainty_score":0.009844363,"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."}}