{"id":"W2041673271","doi":"10.1080/10926488.2001.9678895","title":"Moment-By-Moment Reading of Proverbs in Literal and Nonliteral Contexts","year":2001,"lang":"en","type":"article","venue":"Metaphor and Symbol","topic":"Language, Metaphor, and Cognition","field":"Psychology","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Reading (process); Literal (mathematical logic); Context (archaeology); Ambiguity; Sentence; Meaning (existential); Linguistics; Interpretation (philosophy); Comprehension; Reading comprehension; Literal and figurative language; Statement (logic); Psychology; Trope (literature); Resolution (logic); Computer science; History; Philosophy; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0003240932,0.0001606666,0.0003373518,0.0001623011,0.00003776068,0.00003668893,0.00006458179,0.00008535806,0.000341939],"category_scores_gemma":[0.00001051223,0.0001335082,0.00005392528,0.0001636689,0.00006542256,0.0001262938,0.00002991846,0.0001173244,0.0000096987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001723752,"about_ca_system_score_gemma":0.000006218726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002634648,"about_ca_topic_score_gemma":0.00003299175,"domain_scores_codex":[0.998808,0.0001313082,0.0003372767,0.000314854,0.0001356695,0.0002728861],"domain_scores_gemma":[0.9995852,0.00004223627,0.00008305495,0.000170166,0.00003347316,0.00008584013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00167982,0.001738972,0.3995468,0.0003118486,0.0006920443,0.0003017878,0.09693211,3.469787e-7,0.07761477,0.02141417,0.003966662,0.3958007],"study_design_scores_gemma":[0.02237961,0.002558017,0.8154829,0.0006120529,0.0006561653,0.0006024798,0.02105578,0.0003470512,0.01798151,0.009286316,0.1069649,0.002073315],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983702,0.005259417,0.0001755799,0.00009654694,0.0001768785,0.0003216341,0.00004261223,0.00001724758,0.0102081],"genre_scores_gemma":[0.9940377,0.000211078,0.00008644788,0.0002243491,0.00005239015,0.00006126391,0.00003311718,0.00001402017,0.005279601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4159361,"threshold_uncertainty_score":0.5444308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01180774544606914,"score_gpt":0.2820890615839732,"score_spread":0.270281316137904,"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."}}