{"id":"W2760334374","doi":"10.5430/ijhe.v6n5p88","title":"Are Prospective English Teachers Linguistically Intelligent?","year":2017,"lang":"en","type":"article","venue":"International Journal of Higher Education","topic":"Emotional Intelligence and Performance","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Theory of multiple intelligences; Psychology; Mathematics education; English language; Selection (genetic algorithm); Longitudinal study; Point (geometry); Linguistics; Computer science; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"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":[0.001561913,0.0001694235,0.0002941267,0.001134807,0.0008353032,0.002466345,0.0003509909,0.0007782873,0.002904188],"category_scores_gemma":[0.01062202,0.0003486186,0.0002103124,0.0007956579,0.001108811,0.001853163,0.0008398671,0.001050661,0.0007386158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002772244,"about_ca_system_score_gemma":0.0005772763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002586206,"about_ca_topic_score_gemma":0.00401155,"domain_scores_codex":[0.9990091,0.0002128442,0.0001118306,0.0001281338,0.0002841356,0.0002538405],"domain_scores_gemma":[0.9888483,0.002225264,0.005596546,0.0003680773,0.0008653191,0.002096413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005225448,0.0001764145,0.9845956,0.00002463647,0.000007872118,0.000451092,0.009216184,0.00001426158,0.000213493,0.0001171665,0.0002529824,0.004878079],"study_design_scores_gemma":[0.00000616541,0.0001894333,0.9625105,0.00003750391,0.0000111123,0.000745674,0.03513394,0.00003988807,0.00008953752,0.000132066,0.001092174,0.00001207242],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998481,0.0001998532,0.00002326678,0.0003243722,0.00001230555,0.000004339912,0.00003731719,0.000001971645,0.0009157168],"genre_scores_gemma":[0.9989837,0.000227392,0.00003602282,0.0001315524,0.00001314776,0.000005715052,0.00005627396,0.000001053535,0.0005452021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002904188,"threshold_uncertainty_score":0.009715438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04420894055281804,"score_gpt":0.4231170954594923,"score_spread":0.3789081549066743,"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."}}