{"id":"W2136549419","doi":"10.5539/ijel.v5n2p115","title":"A Cognitive Linguistic Approach to Generics","year":2015,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Conceptualization; Linguistics; Abstraction; Set (abstract data type); Syntax; Sentence; Cognition; Natural (archaeology); Cognitive linguistics; Computer science; Inefficiency; Optimality theory; Cognitive science; Epistemology; Psychology; Philosophy; History; Phonology; Programming language; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002574119,0.0005495339,0.0004508134,0.003904139,0.00221602,0.004909765,0.001615833,0.001728419,0.003740124],"category_scores_gemma":[0.003805302,0.0003215046,0.001160376,0.002211269,0.02044659,0.01124953,0.003001284,0.002760225,0.0003413522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003880549,"about_ca_system_score_gemma":0.001509984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003327535,"about_ca_topic_score_gemma":0.002673918,"domain_scores_codex":[0.9983435,0.000639981,0.0001009734,0.0003527033,0.0003827289,0.0001802163],"domain_scores_gemma":[0.9977768,0.0008609788,0.0003686737,0.000422799,0.0003878187,0.0001827713],"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":[0.000002660858,0.000003926325,0.0001323083,0.00002043474,0.000002823964,0.00003417096,0.001480915,0.0001789092,0.0001113248,0.9952664,0.0003611149,0.002405063],"study_design_scores_gemma":[0.000005040053,0.000009813138,0.0003428627,0.00002648951,0.000007880461,0.0001481492,0.0008306513,0.001533609,0.00009525366,0.9802333,0.01675558,0.00001132443],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06714924,0.003029628,0.542094,0.02110687,0.000406648,0.0001264721,0.0004173444,0.0007060073,0.3649638],"genre_scores_gemma":[0.9131054,0.0008374263,0.07739074,0.001922769,0.0003996256,0.00008896959,0.0002258908,0.00009228093,0.005936881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004909765,"threshold_uncertainty_score":0.02815545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0482023564233276,"score_gpt":0.3401434061624005,"score_spread":0.2919410497390729,"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."}}