{"id":"W2252218513","doi":"","title":"Literal and Metaphorical Sense Identification through Concrete and Abstract Context","year":2011,"lang":"en","type":"article","venue":"NPARC","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":244,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Ministry of Defense; Atomic Energy of Canada Limited","keywords":"Literal (mathematical logic); Computer science; Metaphor; Natural language processing; Adjective; Context (archaeology); Artificial intelligence; Linguistics; Noun; Inference; Word (group theory); Algorithm","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001989149,0.0001043403,0.0001485785,0.00003569096,0.00006210803,0.0000390416,0.00003978564,0.00009519564,0.002131835],"category_scores_gemma":[0.00002924649,0.00008975135,0.00003589557,0.00005839726,0.0001152067,0.0001603477,0.00001776182,0.00011596,0.0001711038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006379934,"about_ca_system_score_gemma":0.000005142475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001647737,"about_ca_topic_score_gemma":0.000007953138,"domain_scores_codex":[0.9991997,0.00007989929,0.0001987898,0.0002720479,0.00008789268,0.000161693],"domain_scores_gemma":[0.9995658,0.00006465699,0.00007522087,0.0001813314,0.00004926143,0.00006376496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001044603,0.0001697966,0.005138151,0.000101496,0.0006227684,0.000479579,0.1815644,6.881382e-9,0.1758946,0.3032414,0.01319673,0.3185464],"study_design_scores_gemma":[0.005778348,0.0006369948,0.668413,0.00007141392,0.000721084,0.001048465,0.02217828,0.00005523743,0.03908144,0.2300556,0.03076704,0.001193034],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.891738,0.001006876,0.0002687928,0.00008796332,0.0002947145,0.0001400837,0.00001948479,0.00004401807,0.1064001],"genre_scores_gemma":[0.9974171,0.00006958964,0.0005405477,0.0004439165,0.00009084762,0.00002268261,0.0000174042,0.00001215714,0.001385738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6632749,"threshold_uncertainty_score":0.9987804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04653668823200464,"score_gpt":0.2967097163552999,"score_spread":0.2501730281232952,"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."}}