{"id":"W4367672474","doi":"10.1101/2023.05.01.538971","title":"Quantifying marine larval dispersal to assess MPA network connectivity and inform future national and transboundary planning efforts","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Marine and coastal plant biology","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Tula Foundation; University of British Columbia; Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada; Institut Nordique De Recherche En Environnement Et En Santé Au Travail","keywords":"Biological dispersal; Marine protected area; Metapopulation; Marine spatial planning; Marine reserve; Biodiversity; Habitat; Ecology; Environmental resource management; Environmental science; Geography; Biology; Population","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0009137117,0.0004004998,0.0002966484,0.001116899,0.0004650876,0.0009871047,0.0007263331,0.0004493317,0.00195429],"category_scores_gemma":[0.003894105,0.0002324063,0.0003730585,0.001001192,0.0003398212,0.001169313,0.0008312237,0.0005526732,0.0001294456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002478532,"about_ca_system_score_gemma":0.001998541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2910736,"about_ca_topic_score_gemma":0.4344579,"domain_scores_codex":[0.9997489,0.0001138944,0.00001396942,0.00004892529,0.00003509341,0.000039256],"domain_scores_gemma":[0.9988095,0.0004119743,0.0002790282,0.00009326028,0.0002413257,0.0001650506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00002634242,0.00005720602,0.3768822,0.00006338619,0.0001494676,0.00006075308,0.0001489944,0.6036206,0.0007395328,0.002327108,0.001030506,0.01489392],"study_design_scores_gemma":[0.000008923876,0.000034326,0.09042498,0.00004873128,0.00004711236,0.00001842522,0.000379137,0.9056187,0.0003159831,0.001839825,0.001244158,0.00001976085],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9597729,0.000345944,0.0327847,0.00057655,0.00001936886,0.0000610575,0.001493453,0.0001738537,0.004772254],"genre_scores_gemma":[0.98829,0.0001040467,0.01082245,0.00003062791,0.000002254056,0.00001949956,0.0004119213,0.00001118822,0.0003080726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2910736,"threshold_uncertainty_score":0.5787588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.037869117109766,"score_gpt":0.2449088169400245,"score_spread":0.2070396998302585,"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."}}