{"id":"W7083590383","doi":"10.1016/j.rcim.2025.103145","title":"CCM-FCC: LLM-powered cognition-centered AI agent framework for proactive human-robot collaboration","year":2025,"lang":"en","type":"article","venue":"Robotics and Computer-Integrated Manufacturing","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Fundamental Research Funds for the Central Universities; National University's Basic Research Foundation of China; National Natural Science Foundation of China","keywords":"Task (project management); Key (lock); Generalization; Semantics (computer science); Cognition; Cognitive architecture; Core (optical fiber); Cognitive model","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002251416,0.0003462766,0.0003609966,0.0001571861,0.0005438411,0.0006531887,0.0005158401,0.0002271829,0.00001241437],"category_scores_gemma":[0.0000623723,0.0003270979,0.0001001312,0.0003067378,0.00006336696,0.0002866366,0.0003062761,0.0003665304,0.000004101571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008651704,"about_ca_system_score_gemma":0.0001061914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001602246,"about_ca_topic_score_gemma":0.000009116616,"domain_scores_codex":[0.9981533,0.0000768198,0.000418741,0.000735458,0.0001689309,0.0004467041],"domain_scores_gemma":[0.9986413,0.0002275643,0.0001806068,0.0004474858,0.0003841813,0.0001189303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002417878,0.001608307,0.000246491,0.001182102,0.001410362,0.0001428168,0.002818761,0.1079085,0.00497962,0.7732877,0.01121924,0.09495439],"study_design_scores_gemma":[0.002106486,0.0004321504,0.001626249,0.0008873848,0.0001296032,0.0000343467,0.0003137769,0.5649369,0.1478941,0.2711326,0.009555935,0.0009504825],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004622526,0.0001083951,0.9890654,0.003632993,0.0008514405,0.0006964442,0.00001475406,0.0002511668,0.0007568463],"genre_scores_gemma":[0.8329235,0.00002078086,0.1652418,0.0009907356,0.0001302542,0.00007157282,0.00009508539,0.000008299059,0.0005179885],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.828301,"threshold_uncertainty_score":0.9999181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02015274086752269,"score_gpt":0.2735121805611317,"score_spread":0.253359439693609,"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."}}