{"id":"W2799282311","doi":"10.26685/urncst.39","title":"Research Fundamentals: Data Collection, Data Analysis, and Ethics","year":2018,"lang":"en","type":"article","venue":"Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Publishing; Data collection; Key (lock); Data science; Engineering ethics; Computer science; Management science; Sociology; Social science; Political 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","open_science","research_integrity"],"consensus_categories":["metaresearch","sts"],"category_scores_codex":[0.1886212,0.0002065655,0.0006916645,0.004194257,0.003656758,0.0007441886,0.003158324,0.001167484,0.00005107986],"category_scores_gemma":[0.1445313,0.0001438213,0.00004772411,0.0167659,0.04034778,0.0009003505,0.01028687,0.02638922,0.00003067244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003015113,"about_ca_system_score_gemma":0.004647541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004954496,"about_ca_topic_score_gemma":0.006576666,"domain_scores_codex":[0.9879712,0.00172062,0.001248698,0.002076232,0.005322283,0.001660995],"domain_scores_gemma":[0.9472978,0.0374468,0.0002859005,0.003651658,0.009553241,0.001764639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001088882,0.001100992,0.7859156,0.0002127292,0.0008186093,0.0006747094,0.000182774,1.016502e-7,0.001536457,0.04389481,0.01274236,0.151832],"study_design_scores_gemma":[0.003884621,0.004947112,0.142656,0.0008407545,0.0002225296,0.001536032,0.003981131,0.02161288,0.0002736175,0.8045222,0.01510989,0.0004133073],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5564864,0.005224796,0.000104736,0.4357922,0.0003415867,0.0005870241,0.00002042429,0.00004776002,0.001395111],"genre_scores_gemma":[0.9111935,0.08396185,0.002966832,0.0003961563,0.0003719843,0.000005210481,0.00001650975,0.00001338339,0.001074517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7606273,"threshold_uncertainty_score":0.9977177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7226965072368479,"score_gpt":0.6857643166640438,"score_spread":0.03693219057280406,"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."}}