{"id":"W4403665894","doi":"10.2139/ssrn.4959395","title":"Building Kinesthetic Intelligence Dance in Conflict-Resolution Education","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Educational Challenges and Innovations","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Kinesthetic learning; Dance; Theory of multiple intelligences; Resolution (logic); Psychology; Conflict resolution; Computer science; Visual arts; Artificial intelligence; Sociology; Pedagogy; Art; Social science","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":[0.0009000286,0.00009255639,0.00007303959,0.0003221058,0.0001047979,0.0002030253,0.0004752042,0.00004126026,0.000006021183],"category_scores_gemma":[0.00003904504,0.00008793519,0.00004035799,0.0008569844,0.00002217422,0.0006835738,0.00003685124,0.0009933352,0.00003447377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009017839,"about_ca_system_score_gemma":0.004082317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003768656,"about_ca_topic_score_gemma":0.0001177989,"domain_scores_codex":[0.9985169,0.00004164804,0.0002354195,0.0002269049,0.0001866752,0.000792512],"domain_scores_gemma":[0.9995734,0.00005104888,0.00005537425,0.0001659856,0.0001161223,0.00003805555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[7.84029e-7,0.00003828256,0.00003821259,0.000005628952,0.000005909096,6.824514e-7,0.0002416177,0.000245068,0.0001585414,0.8806245,0.00008043076,0.1185603],"study_design_scores_gemma":[0.00004235265,0.0000880512,0.0008769822,0.0001534916,0.000003657882,0.0006676548,0.0006427402,0.02363195,0.00009083985,0.9447687,0.02887736,0.0001561973],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03838217,0.0237564,0.9192386,0.01636833,0.001211395,0.00009188746,2.446853e-7,0.00006674368,0.0008842441],"genre_scores_gemma":[0.9883705,0.004447348,0.005965067,0.0001665217,0.0003574264,0.00001622343,0.00000138666,0.000008974377,0.0006666035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9499883,"threshold_uncertainty_score":0.7241856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02119353822888669,"score_gpt":0.3187382054412368,"score_spread":0.2975446672123501,"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."}}