{"id":"W4410851676","doi":"10.1101/2025.05.28.25328509","title":"From warehouse to ward: Applying implementation research methods to the device identification, qualification, distribution, and management process within the NEST360 alliance","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Warehouse; Identification (biology); Distribution (mathematics); Process management; Data warehouse; Computer science; Business; Operations management; Data science; Database; Engineering; Marketing; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1979855,0.001034026,0.001180554,0.006972193,0.00644612,0.01193468,0.004492208,0.002064434,0.004596865],"category_scores_gemma":[0.1984482,0.001338658,0.001942691,0.007933868,0.006448213,0.0103931,0.00874598,0.004037483,0.0007035013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01372673,"about_ca_system_score_gemma":0.03262549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007657837,"about_ca_topic_score_gemma":0.009425665,"domain_scores_codex":[0.768006,0.2066282,0.008040155,0.005228883,0.007202854,0.004893997],"domain_scores_gemma":[0.7313986,0.2218772,0.01219538,0.01144407,0.01970218,0.003382522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.000366976,0.003799682,0.0622439,0.005522737,0.0003282551,0.0007180271,0.5959982,0.002603415,0.001395013,0.03952027,0.003365162,0.2841384],"study_design_scores_gemma":[0.0004732763,0.003265392,0.04410508,0.005666513,0.0004289071,0.0001967106,0.8943537,0.01245022,0.002872121,0.01642606,0.0195915,0.0001705639],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7200701,0.0008828019,0.1999427,0.006909867,0.00020911,0.04173319,0.0007982188,0.0002964236,0.02915766],"genre_scores_gemma":[0.6884062,0.0007098622,0.2764571,0.001286113,0.00003060463,0.03112742,0.000336751,0.00008790098,0.001558081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1979855,"threshold_uncertainty_score":0.9890266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07666386137251285,"score_gpt":0.4439941239269048,"score_spread":0.3673302625543919,"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."}}