{"id":"W2991578290","doi":"10.5703/1288284317144","title":"The Time Has Come... To Build, Reflect, and Analyze Connections Between Qualitative and Quantitative Data","year":2020,"lang":"en","type":"article","venue":"","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Purdue Pharma (Canada)","funders":"","keywords":"Computer science; Extant taxon; Transparency (behavior); Accountability; Process (computing); Process management; Qualitative property; Data science; Management science; Knowledge management; Engineering; Political science","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"],"consensus_categories":[],"category_scores_codex":[0.005800507,0.0001181268,0.0002743308,0.00009096548,0.0006307367,0.001001657,0.001047339,0.00002682159,0.0001583462],"category_scores_gemma":[0.009031463,0.00007012862,0.00002234255,0.0008429869,0.0003575888,0.0006016765,0.001693034,0.0001036508,0.0006185007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008637133,"about_ca_system_score_gemma":0.00003009103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003475978,"about_ca_topic_score_gemma":0.0009302837,"domain_scores_codex":[0.9972425,0.0008227788,0.0004761596,0.0006796434,0.0005904335,0.0001885512],"domain_scores_gemma":[0.9892288,0.009436226,0.0001245058,0.0008166338,0.0001461583,0.0002476502],"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":[0.00009136547,0.00002407669,0.0006657703,0.000007311053,0.0002063159,0.000002845113,0.02872225,0.000007539253,0.0001202055,0.243366,0.7058638,0.02092248],"study_design_scores_gemma":[0.0002753296,0.0003082284,0.003272479,0.000005609474,0.00004721907,6.327646e-7,0.06162993,0.002356502,0.00003291128,0.03194682,0.8999455,0.0001788228],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.07547284,0.0005361898,0.2723074,0.623787,0.0001513476,0.001134245,0.002962861,0.0001523786,0.02349575],"genre_scores_gemma":[0.9414671,0.0001285143,0.03303207,0.0153549,0.0001589703,0.00002734109,0.0002725016,0.00002415049,0.009534417],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8659943,"threshold_uncertainty_score":0.9993159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6070544362019351,"score_gpt":0.5467733598393073,"score_spread":0.06028107636262781,"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."}}