{"id":"W2783735091","doi":"10.1109/bigdata.2017.8258529","title":"Big data in psychology: Using word embeddings to study theory-of-mind","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Concreteness; Word (group theory); Reliability (semiconductor); Reading (process); Big data; Computer science; Cognitive psychology; Natural language processing; Psychology; Artificial intelligence; Cognitive science; Linguistics; Data mining; Philosophy","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":[0.006819345,0.0009033034,0.0008502821,0.005594592,0.0009425123,0.003474228,0.001043517,0.00130063,0.001164343],"category_scores_gemma":[0.07506175,0.000450065,0.001200539,0.005240828,0.002710343,0.008493736,0.003453112,0.002659113,0.0002337872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001027056,"about_ca_system_score_gemma":0.0009351831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001140359,"about_ca_topic_score_gemma":0.001230308,"domain_scores_codex":[0.9951085,0.00330419,0.0003078714,0.0005514034,0.0006369753,0.00009094482],"domain_scores_gemma":[0.9116796,0.07362989,0.00410354,0.007169735,0.002536889,0.0008803328],"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":[0.0004900971,0.0007128417,0.1017739,0.002153571,0.001634142,0.0004104364,0.01167158,0.04398943,0.005580198,0.3806981,0.007058845,0.4438269],"study_design_scores_gemma":[0.00003447583,0.0001903832,0.01285745,0.0002961801,0.0001287321,0.0001860952,0.002103996,0.1737736,0.002005633,0.801578,0.006757269,0.00008819038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1227077,0.003246943,0.8641672,0.003572842,0.0004780293,0.000245726,0.001617803,0.0005158895,0.003447956],"genre_scores_gemma":[0.6741192,0.001006122,0.3218083,0.0004499162,0.0002510393,0.0005532961,0.001307016,0.0001157552,0.00038947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006819345,"threshold_uncertainty_score":0.03606462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1901567129325514,"score_gpt":0.4556427411724217,"score_spread":0.2654860282398703,"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."}}