{"id":"W3207975697","doi":"10.3390/educsci11100647","title":"Patterns of Scientific Reasoning Skills among Pre-Service Science Teachers: A Latent Class Analysis","year":2021,"lang":"en","type":"article","venue":"Education Sciences","topic":"Science Education and Pedagogy","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Latent class model; Class (philosophy); Mathematics education; Scientific reasoning; Psychology; Sample (material); Science education; Complement (music); Computer science; Artificial intelligence; Chemistry; Machine learning","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":[0.003123151,0.0003403945,0.0005385307,0.002807605,0.000769069,0.001491537,0.0005652221,0.0007023444,0.002650232],"category_scores_gemma":[0.01209147,0.0002778256,0.0007038387,0.001405385,0.001125765,0.0009691008,0.001473489,0.000952473,0.0003824953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008312882,"about_ca_system_score_gemma":0.001189978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007183194,"about_ca_topic_score_gemma":0.007278359,"domain_scores_codex":[0.9973102,0.000532547,0.0002928909,0.0003950706,0.0009337449,0.0005355586],"domain_scores_gemma":[0.9893798,0.004326592,0.002655525,0.0009329404,0.001699149,0.001006071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001439115,0.0002742737,0.9825817,0.00001941011,0.00003240111,0.00005459958,0.008629958,0.00008959134,0.0007465379,0.0001126659,0.0001323839,0.007182478],"study_design_scores_gemma":[0.000008447032,0.0001609584,0.9926654,0.000008866185,0.000007257394,0.00007149435,0.00580289,0.0007620855,0.0001786588,0.0001251829,0.0001998774,0.000008920875],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995567,0.0000123504,0.0001748536,0.00001908175,0.000001227236,0.00001694342,0.00004779733,0.000003353606,0.0001676588],"genre_scores_gemma":[0.9996556,0.00000910059,0.0001055033,0.000003965098,0.000001097747,0.00002773471,0.0001041017,0.000002268407,0.00009068158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007183194,"threshold_uncertainty_score":0.01651698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05372129138866755,"score_gpt":0.4195961633479385,"score_spread":0.3658748719592709,"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."}}