{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001763269,0.001876944,0.001191142,0.005706456,0.001430093,0.00341177,0.00221989,0.003041276,0.006494854],"category_scores_gemma":[0.006588105,0.0004157164,0.001561849,0.002997875,0.0009275824,0.005493876,0.002938551,0.001764891,0.004654714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006603635,"about_ca_system_score_gemma":0.001023232,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003286275,"about_ca_topic_score_gemma":0.007248081,"domain_scores_codex":[0.9976737,0.0005236171,0.0002703637,0.0008922008,0.0004698565,0.0001702258],"domain_scores_gemma":[0.9970338,0.001533188,0.0002245592,0.0006264303,0.0004002293,0.0001818765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001775327,0.001111238,0.04728775,0.001990124,0.0005729875,0.0007737918,0.001532937,0.007677844,0.04100349,0.008540703,0.04540693,0.8423269],"study_design_scores_gemma":[0.000666173,0.0009164908,0.08361784,0.0005251585,0.0005014836,0.004471534,0.006711761,0.6528077,0.08082028,0.05806144,0.1105577,0.0003424877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6400316,0.009933613,0.2684825,0.002216985,0.0007328751,0.001256662,0.01916056,0.03185879,0.02632652],"genre_scores_gemma":[0.5345218,0.0009036047,0.4185593,0.0003620515,0.0001419157,0.0004528869,0.03865185,0.000502709,0.005903872],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006494854,"threshold_uncertainty_score":0.02172744,"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."}}