{"id":"W4415352928","doi":"10.1101/2025.10.19.683322","title":"AquaX: An enhanced and revised AquaMaps framework to model marine species distributions and biodiversity","year":2025,"lang":"","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; Dalhousie University; University of British Columbia","funders":"","keywords":"Biodiversity; Environmental niche modelling; Species distribution; Range (aeronautics); Habitat; Biogeography; Ecological niche; Aquatic biodiversity research; Ecosystem; Global biodiversity","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":[0.0009658429,0.0008033028,0.0005093223,0.0008258829,0.0004553665,0.001327291,0.002035888,0.0008018505,0.005443644],"category_scores_gemma":[0.002257633,0.0004992347,0.001285194,0.0008134414,0.0004707391,0.001477581,0.0017216,0.0008873195,0.0008541787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008227403,"about_ca_system_score_gemma":0.001143116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02707798,"about_ca_topic_score_gemma":0.0226242,"domain_scores_codex":[0.9997624,0.00009919611,0.00001896364,0.00004558313,0.00005006929,0.00002387883],"domain_scores_gemma":[0.9995443,0.0002337333,0.00003770861,0.00004924245,0.0000994701,0.0000355116],"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":[0.00002937941,0.00001736527,0.001874664,0.00007012502,0.00006683009,0.00008801051,0.00006042549,0.9694759,0.0004178586,0.01333936,0.003097051,0.01146299],"study_design_scores_gemma":[0.000005857587,0.00000504265,0.0001584205,0.000009488879,0.000005575342,0.00001599149,0.0000104183,0.9905234,0.00008769475,0.005782643,0.003390433,0.000005024188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05299511,0.0005558745,0.921829,0.0007651466,0.0001146539,0.0001266298,0.007373607,0.007504793,0.008735062],"genre_scores_gemma":[0.5030168,0.0007730426,0.4801988,0.000309157,0.00009111235,0.0007009875,0.00942905,0.001135294,0.004345876],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02707798,"threshold_uncertainty_score":0.0538407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02137602909135062,"score_gpt":0.2307180224394671,"score_spread":0.2093419933481165,"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."}}