{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001657982,0.0007748558,0.0005335258,0.001721783,0.001040586,0.004077495,0.001884807,0.001575606,0.005015074],"category_scores_gemma":[0.002341635,0.0003096086,0.001301566,0.0009836667,0.008008323,0.006496457,0.002215489,0.002696493,0.0008028257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001870033,"about_ca_system_score_gemma":0.001584186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00272639,"about_ca_topic_score_gemma":0.001391522,"domain_scores_codex":[0.9990319,0.0003866206,0.00005688143,0.0002341713,0.0002145037,0.00007589961],"domain_scores_gemma":[0.9988193,0.000677958,0.0000914639,0.0001972516,0.000139789,0.00007423266],"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":[0.000003288264,0.000005950008,0.00005124311,0.00003478304,0.000006964442,0.00002712163,0.0001571222,0.002304416,0.0001718361,0.9924544,0.0003656351,0.004417264],"study_design_scores_gemma":[0.000003318084,0.000004440396,0.00004717952,0.00001354001,0.00000335084,0.00003029368,0.00004124209,0.006553577,0.0001140809,0.9879775,0.005206955,0.000004481624],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0075203,0.002911703,0.8820702,0.01136022,0.0002012941,0.00007990863,0.0001817639,0.0003858721,0.09528856],"genre_scores_gemma":[0.5411088,0.003422751,0.4354256,0.002362735,0.0008066723,0.0006191746,0.0004121425,0.0001545276,0.0156875],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005015074,"threshold_uncertainty_score":0.0167771,"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."}}