{"id":"W74079051","doi":"10.1007/978-3-319-14102-2_2","title":"Semantics, Concepts, and Meta-cognition: Attributing Properties and Meanings to Complex Concepts","year":2015,"lang":"en","type":"book-chapter","venue":"Studies in morphology","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Lexical semantics; Semantics (computer science); Linguistics; Interpretation (philosophy); Noun; Cognitive semantics; Lexicology; Psychology; Cognition; Meaning (existential); Noun phrase; Cognitive science; Natural language processing; Computer science; Lexical item; Epistemology; Philosophy","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000683075,0.0005643749,0.001621829,0.0002359307,0.0001745124,0.00002591585,0.0001599936,0.0004184202,0.001353368],"category_scores_gemma":[0.0003585324,0.000460704,0.0001084049,0.0000595754,0.001669849,0.00005860842,0.0004484219,0.0005021148,0.0001620339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006619612,"about_ca_system_score_gemma":0.00002717141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007986835,"about_ca_topic_score_gemma":0.0002652205,"domain_scores_codex":[0.9975521,0.0002039172,0.0006166347,0.0008945199,0.000230376,0.0005024445],"domain_scores_gemma":[0.9985154,0.0002755759,0.0002817459,0.0003171845,0.000482303,0.0001277866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001456746,0.0002705514,0.0008453811,0.001409612,0.03382002,0.005150398,0.1997645,0.000004176731,0.00169972,0.4566696,0.2809624,0.01794685],"study_design_scores_gemma":[0.01096789,0.004029408,0.00218804,0.001334029,0.02975512,0.004457311,0.1315693,0.000009324584,0.0003465497,0.1576766,0.651877,0.005789462],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03476455,0.2900315,0.0001633003,0.003820254,0.003347605,0.003207313,0.001044013,0.0003125416,0.663309],"genre_scores_gemma":[0.8420131,0.001852784,0.00055821,0.004195372,0.0006415545,0.0003253372,0.0001749728,0.0001314719,0.1501072],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8072485,"threshold_uncertainty_score":0.9997845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2926893665171089,"score_gpt":0.3964731570450994,"score_spread":0.1037837905279905,"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."}}