{"id":"W2093518356","doi":"10.1109/coginf.2011.6016137","title":"A cognitive informatics framework for language understanding","year":2011,"lang":"en","type":"article","venue":"","topic":"Cognitive Computing and Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Embodied cognition; Computer science; Cognitive science; Informatics; Meaning (existential); Cognition; Process (computing); Artificial intelligence; Natural language processing; Programming language; Psychology","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":[0.0002185437,0.0000955861,0.0001009039,0.00006646083,0.0001283878,0.00007904259,0.0002681891,0.00006187059,0.00003116153],"category_scores_gemma":[0.0001656725,0.00008352506,0.00005864315,0.0002203513,0.00003143343,0.0002062515,0.0001589303,0.0001175086,0.00003415682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002371617,"about_ca_system_score_gemma":0.00002545018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005407307,"about_ca_topic_score_gemma":0.000003903372,"domain_scores_codex":[0.9993415,0.00001760341,0.000160305,0.0001309066,0.00009808532,0.0002516198],"domain_scores_gemma":[0.9988987,0.0007593904,0.00006850893,0.0001341616,0.00007258955,0.00006662542],"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":[0.00002497633,0.0000503737,0.0003784259,0.00002390384,0.00004393112,0.000005241779,0.03254773,0.000001636114,0.000001544834,0.8740914,0.0004690219,0.09236184],"study_design_scores_gemma":[0.001866491,0.0006547068,0.001381157,0.0009997914,0.00006228942,0.00003498351,0.03683683,0.4071332,0.002568911,0.5473306,0.0001969535,0.0009341149],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005094852,0.0000467433,0.9635272,0.00003197387,0.000232723,0.000185191,0.000001984602,0.0002458182,0.03063351],"genre_scores_gemma":[0.7746575,0.000002926642,0.224514,0.0006550805,0.00005795109,0.000009581999,0.000001860268,0.000005285417,0.00009573479],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7695627,"threshold_uncertainty_score":0.3406053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1207837432583944,"score_gpt":0.3053653086408707,"score_spread":0.1845815653824763,"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."}}