{"id":"W2519597521","doi":"10.3999/jscpt.44.47","title":"Current Status and Future Expectations of Using Remote Source Data Verification for Improving the Efficiency of Clinical Trials","year":2013,"lang":"en","type":"article","venue":"Rinsho yakuri/Japanese Journal of Clinical Pharmacology and Therapeutics","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Association of Canadian Archivists","funders":"","keywords":"Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.006515316,0.000123518,0.0006240533,0.00009431478,0.00008387916,0.0000122497,0.0002670128,0.0001430382,0.00001221896],"category_scores_gemma":[0.0005060103,0.00008187201,0.0001096927,0.0002091556,0.0003674145,0.0002063227,0.00006144396,0.0004684041,2.365922e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001167822,"about_ca_system_score_gemma":0.00009719074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003247259,"about_ca_topic_score_gemma":1.195967e-7,"domain_scores_codex":[0.9965774,0.0003990438,0.002578439,0.0001536516,0.0001324591,0.0001589965],"domain_scores_gemma":[0.9958215,0.002089174,0.001247199,0.0002232484,0.0005595906,0.00005923867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004316594,0.0002607145,0.00564794,0.0001644205,0.0003932262,3.608562e-7,0.001051752,0.00006594067,0.2956375,0.0004163374,0.0001841746,0.695746],"study_design_scores_gemma":[0.02012164,0.002719745,0.07335223,0.000223974,0.003275754,0.0001542416,0.01021631,0.5868148,0.2332661,0.005328747,0.06352729,0.0009992264],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8695157,0.003175841,0.1257614,0.0002223422,0.0008899454,0.0003963035,0.00001539778,0.0000135398,0.000009570037],"genre_scores_gemma":[0.9933154,0.002383677,0.00344218,0.000104915,0.0007269125,0.000003129744,0.000008500447,0.00001371126,0.000001583889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6947468,"threshold_uncertainty_score":0.3338644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2168482143777374,"score_gpt":0.4907498686909708,"score_spread":0.2739016543132334,"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."}}