{"id":"W7125650556","doi":"10.1109/cascon66301.2025.00079","title":"Supervised Semantic Similarity-Based Conflict Detection Algorithm: S3CDA","year":2025,"lang":"","type":"article","venue":"","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"IBM (Canada); Toronto Metropolitan University","funders":"","keywords":"Pattern recognition (psychology); Feature (linguistics); Noise (video); Semantics (computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001019572,0.0008374649,0.001633429,0.00143039,0.0009486456,0.001043798,0.003068311,0.001523655,0.005701262],"category_scores_gemma":[0.002688447,0.0003907793,0.0007332765,0.001006881,0.0007571969,0.001051468,0.002057042,0.001414996,0.001196956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008491073,"about_ca_system_score_gemma":0.003328562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007082485,"about_ca_topic_score_gemma":0.009638954,"domain_scores_codex":[0.9990884,0.0001351398,0.0000597813,0.0003008042,0.0003107851,0.0001051212],"domain_scores_gemma":[0.9987139,0.0003256658,0.0001134537,0.0001825799,0.0005413015,0.0001230891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005890329,0.0007388946,0.003713572,0.0001408557,0.0001546508,0.0001341145,0.0001014997,0.1179608,0.01360005,0.007531357,0.01181156,0.8435236],"study_design_scores_gemma":[0.0000513821,0.00008112995,0.0004258034,0.000007288018,0.00001944534,0.00007174833,0.00002239972,0.990555,0.004170386,0.003209946,0.001371842,0.00001377819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03720851,0.0003015475,0.9548764,0.0002601774,0.0001579612,0.0003121057,0.0002065406,0.00322643,0.003450434],"genre_scores_gemma":[0.457416,0.00009054449,0.5364565,0.000343398,0.00005928321,0.0003752851,0.0006925692,0.0001945521,0.004371922],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007082485,"threshold_uncertainty_score":0.01907265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035180397387599,"score_gpt":0.2674203222397192,"score_spread":0.2470685182658432,"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."}}