{"id":"W3211131380","doi":"10.1515/9783110630367-011","title":"Using Literal Underpinnings to Help Learners Remember Figurative Idioms: Does the Connection Need to Be Crystal Clear?","year":2019,"lang":"en","type":"book-chapter","venue":"","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Strong","keywords":"Literal and figurative language; Literal (mathematical logic); Connection (principal bundle); Psychology; Linguistics; Philosophy; Mathematics; Geometry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007079243,0.000474462,0.0003022003,0.0003532312,0.0002836404,0.002761046,0.0009824169,0.001007704,0.01210611],"category_scores_gemma":[0.003173063,0.0002824121,0.000301226,0.0002858551,0.00147334,0.008901538,0.001088784,0.003585338,0.004565689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003216251,"about_ca_system_score_gemma":0.0008853522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005291735,"about_ca_topic_score_gemma":0.001686682,"domain_scores_codex":[0.9998491,0.00003972037,0.0000102443,0.0000263067,0.00005461973,0.00002001785],"domain_scores_gemma":[0.9992844,0.0004768214,0.00004129838,0.00007516381,0.00007582155,0.00004648052],"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":[0.0001290547,0.0003798699,0.002086398,0.0007555973,0.00002657124,0.0006678216,0.01151198,0.0002099453,0.01150642,0.11077,0.04833012,0.8136262],"study_design_scores_gemma":[0.0001697948,0.0004829057,0.005666358,0.001379017,0.0001231074,0.004262703,0.01567688,0.003489265,0.01738243,0.4959095,0.4553468,0.0001113412],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2248726,0.02937393,0.198832,0.04309772,0.003756705,0.0002980258,0.0003885167,0.003388653,0.4959919],"genre_scores_gemma":[0.5807203,0.0257818,0.2167872,0.006860738,0.0004287935,0.000185876,0.0007339258,0.0007907294,0.1677106],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01210611,"threshold_uncertainty_score":0.04049903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05641464963315795,"score_gpt":0.3355133871384332,"score_spread":0.2790987375052753,"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."}}