{"id":"W4411964776","doi":"10.2218/eor.2025.10958","title":"Open Science, Data, and Methodologies: Lessons learned from the NIHR-RESPIRE Network in Asia","year":2025,"lang":"en","type":"article","venue":"Edinburgh Open Research","topic":"Academic Publishing and Open Access","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"Government of the United Kingdom","keywords":"Data science; Open science; Epistemology; Computer science; Philosophy; Physics; Astronomy","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","open_science"],"consensus_categories":[],"category_scores_codex":[0.3030442,0.001029514,0.001509753,0.002793659,0.007347499,0.02980236,0.007420456,0.007223152,0.003910048],"category_scores_gemma":[0.1622871,0.0009132626,0.001782827,0.005421127,0.0283429,0.03925954,0.03192318,0.02303213,0.001771434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0133931,"about_ca_system_score_gemma":0.08484821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01527087,"about_ca_topic_score_gemma":0.01838244,"domain_scores_codex":[0.8356531,0.1272668,0.009574967,0.005919468,0.0152155,0.006370245],"domain_scores_gemma":[0.5291824,0.3365914,0.01143266,0.03797695,0.05057103,0.03424558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003560003,0.0005028282,0.02296997,0.005910044,0.0002558704,0.003831453,0.2148153,0.002800744,0.0012584,0.2305881,0.1230985,0.3936128],"study_design_scores_gemma":[0.0000828689,0.0002884635,0.00537661,0.01233691,0.00008615744,0.001518992,0.1022459,0.001826587,0.001654379,0.2020112,0.6723895,0.0001823266],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01936435,0.02558802,0.04098526,0.8811045,0.002749911,0.0003916848,0.0004641896,0.0003045205,0.02904762],"genre_scores_gemma":[0.3791251,0.07257483,0.2936353,0.2272246,0.00445872,0.001971982,0.001751029,0.001275111,0.0179833],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9925795,"threshold_uncertainty_score":0.8594705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7883018652569722,"score_gpt":0.6625047773775982,"score_spread":0.125797087879374,"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."}}