{"id":"W4416392445","doi":"10.3897/biss.9.177966","title":"Everywhere Everyone Everything All at Once: Integrating Data Infrastructures and Analysis Workflows for the Upscaling to Global Genetic Monitoring","year":2025,"lang":"","type":"article","venue":"Biodiversity Information Science and Standards","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workflow; Standardization; Harmonization; Data integration; Environmental monitoring; Pipeline (software); Process (computing); Scale (ratio); Visualization; Data management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05514742,0.001751896,0.001335377,0.008722237,0.003033243,0.01508256,0.004760099,0.002552933,0.008016524],"category_scores_gemma":[0.0659143,0.001593466,0.002437584,0.007991657,0.002863245,0.02422903,0.02091184,0.00653445,0.009284806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004308142,"about_ca_system_score_gemma":0.02213146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02156849,"about_ca_topic_score_gemma":0.0191337,"domain_scores_codex":[0.9773574,0.008206672,0.003043414,0.003573216,0.006021375,0.00179792],"domain_scores_gemma":[0.9394335,0.01120429,0.002672415,0.02238633,0.01765081,0.006652663],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005297785,0.0004994803,0.02578145,0.001837461,0.0003897552,0.0004766984,0.008305451,0.007088298,0.01118399,0.06440814,0.1261224,0.753377],"study_design_scores_gemma":[0.0001087642,0.0002249986,0.01836246,0.004458764,0.0003851158,0.0003345346,0.008309863,0.02000508,0.006886832,0.1454543,0.7949916,0.0004777007],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03718823,0.009944188,0.7574006,0.0748983,0.004138827,0.002695068,0.01291043,0.04766405,0.05316031],"genre_scores_gemma":[0.06832361,0.004243353,0.8738732,0.006212286,0.0005963467,0.001325947,0.03357322,0.005886488,0.005965481],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9448526,"threshold_uncertainty_score":0.291651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06889248153765737,"score_gpt":0.3809632779196684,"score_spread":0.312070796382011,"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."}}