{"id":"W4405280959","doi":"10.1371/journal.pcbi.1012660","title":"Bacterial clustering amplifies the reshaping of eutrophic plumes around marine particles: A hybrid data-driven model","year":2024,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"European Commission","keywords":"Cluster analysis; Eutrophication; Environmental science; Ecology; Oceanography; Biology; Computer science; Nutrient; Geology; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001725933,0.00009382917,0.0001548363,0.00005425576,0.00008855796,0.00007452608,0.0003162133,0.00002709593,0.0003418531],"category_scores_gemma":[0.00003189395,0.00006296608,0.000033131,0.00009303563,0.0001105373,0.0001471341,0.0001740543,0.00009035326,0.00006061165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003174707,"about_ca_system_score_gemma":0.00008314526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006971431,"about_ca_topic_score_gemma":0.001111042,"domain_scores_codex":[0.9991209,0.00008126337,0.0002676565,0.0002536447,0.0001109632,0.0001655619],"domain_scores_gemma":[0.9993363,0.0003596367,0.00005800999,0.0001752889,0.00003579721,0.00003498929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001394419,0.00002952101,0.0367256,0.0002301047,0.0002369956,0.00001723384,0.0001986512,0.921013,0.0007968941,0.00348635,0.0007324304,0.03639378],"study_design_scores_gemma":[0.00008691205,0.00006049175,0.004866995,0.00002435762,0.00001723333,0.00002331636,0.00003527998,0.9796369,0.0000149884,0.01397532,0.001182802,0.00007538252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878242,0.0004001586,0.009004085,0.0006242654,0.0003102462,0.0001463645,0.0006954207,0.00005708244,0.0009381864],"genre_scores_gemma":[0.996474,0.00001830383,0.001490462,0.0001674861,0.0002384705,0.000002270809,0.001574853,0.000003569112,0.00003055842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05862392,"threshold_uncertainty_score":0.3743052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06034028420472756,"score_gpt":0.2548823787981641,"score_spread":0.1945420945934365,"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."}}