{"id":"W4410778599","doi":"10.1111/csp2.70035","title":"<scp>FISHGLOB</scp> : A collaborative infrastructure to bridge the gap between scientific monitoring and marine biodiversity conservation","year":2025,"lang":"en","type":"article","venue":"Conservation Science and Practice","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Memorial University of Newfoundland; University of British Columbia; Fisheries and Oceans Canada","funders":"Université de Montpellier; National Science Foundation","keywords":"Bridge (graph theory); Marine biodiversity; Biodiversity; Biodiversity conservation; Marine species; Business; Environmental resource management; Fishery; Environmental science; Ecology; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.0139548,0.001071382,0.0007271476,0.005749807,0.001886408,0.004306788,0.003758098,0.001732074,0.077696],"category_scores_gemma":[0.0248033,0.0006777905,0.0006422226,0.006496811,0.001753249,0.004803765,0.01490108,0.001645912,0.03631322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001760156,"about_ca_system_score_gemma":0.009006101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02282226,"about_ca_topic_score_gemma":0.01624308,"domain_scores_codex":[0.9952558,0.001456686,0.0003011775,0.0007090239,0.001852044,0.0004252833],"domain_scores_gemma":[0.9670863,0.006347165,0.001852726,0.009975983,0.006695518,0.008042298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003139462,0.0001069441,0.005311436,0.0005198265,0.00008374641,0.0002332776,0.00130214,0.001528766,0.004870704,0.009203036,0.8880887,0.08843736],"study_design_scores_gemma":[0.0001070893,0.00005352424,0.009833093,0.0002880448,0.000027233,0.0001133743,0.0004548848,0.005170236,0.002626729,0.007384757,0.9738668,0.00007433089],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.02804852,0.001097395,0.2668895,0.01494346,0.0009554508,0.003486761,0.3007022,0.1845209,0.1993559],"genre_scores_gemma":[0.1173663,0.0006703521,0.2876019,0.004043261,0.0006629101,0.005825575,0.4590481,0.04526323,0.07951839],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.077696,"threshold_uncertainty_score":0.259919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03360836686860961,"score_gpt":0.2831414796766158,"score_spread":0.2495331128080062,"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."}}