{"id":"W2772792681","doi":"10.1177/1558689817743581","title":"Distinct Yet Synergetic Contributors to Mixed Methods Research: Intersections for MMIRA and <i>JMMR</i>","year":2017,"lang":"en","type":"article","venue":"Journal of Mixed Methods Research","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Multimethodology; Sociology; Management science; Computer science; Psychology; Social science; Engineering","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","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3185608,0.0002026809,0.0007839562,0.002093499,0.002525887,0.001766674,0.002355149,0.0001771572,0.000374932],"category_scores_gemma":[0.2276743,0.0001382697,0.0003058504,0.001179926,0.0007427539,0.0008057137,0.0009939679,0.001502298,0.00005694946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003178708,"about_ca_system_score_gemma":0.0009457547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007981876,"about_ca_topic_score_gemma":0.0002207067,"domain_scores_codex":[0.9736955,0.01842763,0.001651345,0.0006108973,0.004618412,0.0009962197],"domain_scores_gemma":[0.9413598,0.04596838,0.0007956965,0.001344418,0.009638664,0.0008930715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007062468,0.0001629329,0.002452062,0.00003298259,0.0001133703,0.00001435487,0.001296765,0.00003333154,0.0328939,0.002714747,0.1106274,0.8489519],"study_design_scores_gemma":[0.002679462,0.003094089,0.0992916,0.0002639605,0.00005950659,0.0001129863,0.01206932,0.005123785,0.04107843,0.1465693,0.6892934,0.0003642325],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2274496,0.0005739001,0.740204,0.0211209,0.004380431,0.001149723,0.00004694772,0.00001195365,0.005062578],"genre_scores_gemma":[0.4138982,0.0001795823,0.5801322,0.00008845379,0.0005161506,0.0001099221,0.000001502263,0.00003061179,0.00504334],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8485877,"threshold_uncertainty_score":0.9992696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7320044775351187,"score_gpt":0.7489588481319771,"score_spread":0.01695437059685845,"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."}}