{"id":"W4409603676","doi":"10.61091/jcmcc127b-239","title":"Construction and optimization method of modern dance movement style feature classification model based on deep learning","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"E-commerce and Technology Innovations","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dance; Movement (music); Style (visual arts); Artificial intelligence; Feature (linguistics); Computer science; Deep learning; Pattern recognition (psychology); Art; Visual arts; Aesthetics; Linguistics; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004779386,0.0007909182,0.0008762259,0.0007795057,0.0003747835,0.0006750193,0.001282207,0.0007662964,0.002509011],"category_scores_gemma":[0.0007494122,0.0005256202,0.001022569,0.0006725054,0.0003868767,0.001043409,0.0008309167,0.001137984,0.0005550819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000946924,"about_ca_system_score_gemma":0.001592861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01932461,"about_ca_topic_score_gemma":0.01308895,"domain_scores_codex":[0.9996696,0.00003257246,0.00002426548,0.0001236736,0.00008905211,0.00006086307],"domain_scores_gemma":[0.9998404,0.0000346314,0.00001787892,0.00001524696,0.00007787105,0.00001406509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000771568,0.00006536433,0.001884438,0.00009032209,0.00009516314,0.00008938683,0.00005326153,0.6736428,0.007609684,0.004320916,0.0030337,0.3090377],"study_design_scores_gemma":[0.00000245352,0.000007522909,0.0001266271,0.000002014628,0.000005996264,0.000006842543,0.000003173671,0.9987516,0.0003758494,0.0005270652,0.0001886335,0.000002201544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01916975,0.0002619296,0.9778789,0.0001499698,0.00003819912,0.00003531238,0.00007381134,0.00086352,0.001528634],"genre_scores_gemma":[0.7674224,0.0005864946,0.2209523,0.0003399204,0.00006987759,0.0003554774,0.0009405484,0.0002243625,0.009108465],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01932461,"threshold_uncertainty_score":0.03842425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01278167651713264,"score_gpt":0.2556448680158121,"score_spread":0.2428631914986795,"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."}}