{"id":"W2737553943","doi":"10.1093/oxfordhb/9780198568971.013.0010","title":"Representation and processing of lexically ambiguous words","year":2012,"lang":"en","type":"book-chapter","venue":"Oxford University Press eBooks","topic":"Reading and Literacy Development","field":"Psychology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ambiguity; Phenomenon; Representation (politics); Context (archaeology); Computer science; Selection (genetic algorithm); Word (group theory); Natural language processing; Presentation (obstetrics); Cognitive psychology; Linguistics; Artificial intelligence; Cognitive science; Psychology; Epistemology; History","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003113657,0.0002402607,0.0002879913,0.0003909935,0.0001547128,0.001570517,0.0003112701,0.0003998074,0.003828748],"category_scores_gemma":[0.003686076,0.0001821464,0.0001616164,0.0004302537,0.0005969697,0.00188211,0.0007785544,0.0004711164,0.0005209203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001578264,"about_ca_system_score_gemma":0.0001412053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002787856,"about_ca_topic_score_gemma":0.0002585331,"domain_scores_codex":[0.9997562,0.00007150004,0.00001330225,0.00006104105,0.00007903571,0.00001893909],"domain_scores_gemma":[0.9985617,0.00108977,0.0001333972,0.00008474454,0.00009511953,0.00003531257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008055834,0.0001512918,0.006802759,0.000822361,0.00006274557,0.0009686945,0.01304946,0.001983262,0.5994104,0.02013106,0.001381545,0.3544307],"study_design_scores_gemma":[0.0002456174,0.001853522,0.3304703,0.0009526347,0.00036898,0.004565903,0.01532734,0.04664846,0.2527012,0.3182556,0.02831092,0.0002995589],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9655944,0.001306411,0.01312288,0.000193275,0.00004806496,0.00001936164,0.00008504623,0.00008364646,0.01954689],"genre_scores_gemma":[0.9929075,0.0004843146,0.004083378,0.00005564767,0.0000203665,0.00001603561,0.0001034183,0.00006527886,0.002264119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003828748,"threshold_uncertainty_score":0.01280838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0387583327247809,"score_gpt":0.269626608806959,"score_spread":0.2308682760821781,"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."}}