{"id":"W3011809652","doi":"10.1016/j.ecss.2020.106713","title":"Deep learning habitat modeling for moving organisms in rapidly changing estuarine environments: A case of two fishes","year":2020,"lang":"en","type":"article","venue":"Estuarine Coastal and Shelf Science","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministère des Forêts, de la Faune et des Parcs; Institut National de la Recherche Scientifique; Environment and Climate Change Canada","funders":"","keywords":"Estuary; Habitat; Environmental science; Sturgeon; Fish migration; Lake sturgeon; Fishery; Ecology; Acipenser; Fish <Actinopterygii>; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005640786,0.0001632378,0.0002264047,0.00009774202,0.0005274841,0.00003235794,0.0002218793,0.0000262253,0.00009264836],"category_scores_gemma":[0.0002467769,0.00015451,0.00003069544,0.0005609904,0.0005977505,0.0005109719,0.001496088,0.0001374353,0.00001141186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004138251,"about_ca_system_score_gemma":0.000008028914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004271983,"about_ca_topic_score_gemma":0.002751827,"domain_scores_codex":[0.9985378,0.00002331481,0.0002616757,0.0005254702,0.0001952563,0.0004565188],"domain_scores_gemma":[0.9996188,0.00007726382,0.00008185437,0.000101986,0.000007892732,0.0001122562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008287677,0.0001830494,0.7604339,0.0001099321,0.00002468894,0.000271222,0.01277018,0.190052,0.01666923,0.0008367912,0.00005197119,0.01851421],"study_design_scores_gemma":[0.001276011,0.0004871615,0.0441562,0.0000230967,0.00002778075,0.00005052389,0.006212392,0.9456346,0.0009497709,0.0006904866,0.0001602928,0.0003317076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9620823,0.00002425998,0.03534736,0.0006964211,0.00004875321,0.0003126726,7.436566e-7,0.00002597555,0.001461517],"genre_scores_gemma":[0.9950181,0.00004887285,0.00436029,0.0003482054,0.00002024716,0.00003068837,0.000001868126,0.0000102271,0.0001615578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7555826,"threshold_uncertainty_score":0.6300737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01158172213344251,"score_gpt":0.2222343167984964,"score_spread":0.2106525946650539,"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."}}