{"id":"W2897423990","doi":"10.1002/tea.21523","title":"Evaluating the effects of analogy enriched text on the learning of science: The importance of learning indexes","year":2018,"lang":"en","type":"article","venue":"Journal of Research in Science Teaching","topic":"Educational Strategies and Epistemologies","field":"Psychology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Education and Early Childhood Development","funders":"Sixth Framework Programme; European Commission","keywords":"Analogy; Conceptual change; Reading (process); Concept learning; Psychology; Test (biology); Mathematics education; Artificial intelligence; Computer science; Epistemology; Linguistics; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":["metaresearch","sts"],"category_scores_codex":[0.07950629,0.00008315431,0.000224758,0.0006211377,0.00147217,0.00007931532,0.002086299,0.00004091436,0.0000477695],"category_scores_gemma":[0.03195847,0.00003719515,0.00006864082,0.002354152,0.0103536,0.0002683738,0.0002545883,0.002034822,0.000002138373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001278983,"about_ca_system_score_gemma":0.001122515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003292074,"about_ca_topic_score_gemma":0.00001709884,"domain_scores_codex":[0.9940043,0.002415347,0.0006353027,0.0002152957,0.002212171,0.0005175906],"domain_scores_gemma":[0.9869028,0.01071682,0.0009418334,0.0003539587,0.00103167,0.00005290729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001900009,0.0001827874,0.5891805,0.00007014018,0.0000339791,0.000006395614,0.0627635,0.002759337,0.2264942,0.1034449,0.000159818,0.01471444],"study_design_scores_gemma":[0.0003400986,0.004536364,0.8382242,0.0005052533,0.000009864193,0.00005764074,0.1396876,0.001978685,0.004878246,0.009591185,0.0001093065,0.00008150787],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895284,0.0004440909,0.00004408774,0.002451253,0.000396442,0.0001748051,1.242378e-7,0.00000244155,0.006958368],"genre_scores_gemma":[0.9994757,0.0000297879,0.0001737421,0.00003440685,0.0001544333,0.000005612519,3.707391e-8,0.000004846095,0.0001215005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2490437,"threshold_uncertainty_score":0.9998278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2132627396254807,"score_gpt":0.5610157559815953,"score_spread":0.3477530163561146,"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."}}