{"id":"W2287020562","doi":"","title":"Protecting Human Research Subjects: A Jurisdictional Analysis","year":2003,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Pledge; Government (linguistics); Public administration; Jurisdiction; Political science; Federalism; Federal jurisdiction; Corporate governance; Scope (computer science); CLARITY; Negotiation; Public relations; Business; Law; Politics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.38187,0.0009751302,0.002055291,0.007529714,0.01650805,0.02085553,0.00694539,0.01972855,0.005188583],"category_scores_gemma":[0.2797016,0.001670467,0.002916173,0.007352046,0.07179868,0.0265689,0.01612991,0.02278435,0.00125673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01552392,"about_ca_system_score_gemma":0.04578794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0169966,"about_ca_topic_score_gemma":0.0137963,"domain_scores_codex":[0.5945311,0.3199986,0.01181568,0.01691159,0.04547291,0.01127013],"domain_scores_gemma":[0.5047266,0.4272394,0.009694115,0.02516501,0.02840848,0.004766287],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000174601,0.00001107903,0.0007031572,0.00009698929,0.00003012536,0.00009600049,0.005043535,0.0001197739,0.00005927644,0.984252,0.003360619,0.006209991],"study_design_scores_gemma":[0.00007613671,0.00008745549,0.001699082,0.001441302,0.0001767775,0.0003979076,0.00569894,0.001076474,0.0004476254,0.8951477,0.09366841,0.00008213787],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02282867,0.02756398,0.2663983,0.4472067,0.002721091,0.001095492,0.0004692141,0.0001633492,0.2315531],"genre_scores_gemma":[0.7171226,0.009462389,0.124469,0.1261254,0.004123783,0.003375808,0.0002647016,0.0002337396,0.01482244],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.61813,"threshold_uncertainty_score":0.7622643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2848670494628717,"score_gpt":0.5198419704920584,"score_spread":0.2349749210291867,"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."}}