{"id":"W2327837586","doi":"10.1177/1558689815570092","title":"Investigator Triangulation","year":2015,"lang":"en","type":"article","venue":"Journal of Mixed Methods Research","topic":"Health Policy Implementation Science","field":"Health Professions","cited_by":350,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Child Health Clinician Scientist Program","keywords":"Triangulation; Computer science; Diversity (politics); Inclusion (mineral); Multimethodology; Psychology; Data science; Management science; Sociology; Mathematics education; Social psychology; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.1499432,0.00007476721,0.0003052149,0.0008529358,0.0004733792,0.00002042307,0.0004367349,0.0001345279,0.000353126],"category_scores_gemma":[0.1597222,0.00005686125,0.00005623642,0.001388276,0.0001790751,0.0003735564,0.0001481084,0.001560459,0.0002566909],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000694729,"about_ca_system_score_gemma":0.009265001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001011688,"about_ca_topic_score_gemma":0.00001907937,"domain_scores_codex":[0.9651693,0.03084424,0.001390451,0.0001359385,0.001735934,0.0007242087],"domain_scores_gemma":[0.9783322,0.01439746,0.0007544081,0.0002901822,0.004351445,0.001874321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002864606,0.00004087963,0.01301638,0.0001405654,0.00002441173,0.00001869056,0.02732968,0.000017778,0.02211649,0.004289721,0.8418398,0.0908791],"study_design_scores_gemma":[0.002740763,0.0004859103,0.01468712,0.0001229883,0.000007586388,0.00002131207,0.01704694,0.0001948357,0.004312227,0.02756277,0.9327261,0.00009139664],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6537874,0.0003413528,0.2219032,0.1022465,0.005195843,0.001485018,0.00001278469,0.00003321317,0.01499473],"genre_scores_gemma":[0.07346095,0.00005591126,0.9138505,0.005649904,0.002575523,0.00005508891,0.000001071858,0.00003407573,0.004316931],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6919473,"threshold_uncertainty_score":0.9963515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9815558471693605,"score_gpt":0.8821782406828093,"score_spread":0.09937760648655125,"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."}}