{"id":"W4402532198","doi":"10.1002/wat2.1752","title":"Food for fish: Challenges and opportunities for quantifying foodscapes in river networks","year":2024,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Water","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Fisheries and Oceans Canada","funders":"","keywords":"Habitat; Environmental resource management; Climate change; Food security; Abiotic component; Foraging; Watershed; Environmental science; Fish <Actinopterygii>; Ecology; Fishery; Computer science; Biology; Agriculture","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":[0.0185241,0.0008031926,0.0008706934,0.004304053,0.001216187,0.006807386,0.002061822,0.001541059,0.002401715],"category_scores_gemma":[0.0591077,0.0005208091,0.0006432824,0.005797514,0.004430102,0.009088708,0.004949308,0.002215317,0.0003174982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002660824,"about_ca_system_score_gemma":0.00279349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02074121,"about_ca_topic_score_gemma":0.03327202,"domain_scores_codex":[0.9917997,0.005436637,0.0005673635,0.001125717,0.0009028762,0.0001677047],"domain_scores_gemma":[0.9393983,0.04294616,0.007480009,0.004665712,0.00476879,0.0007409939],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007028273,0.0001192723,0.3393278,0.004125295,0.000872631,0.0002507568,0.008403744,0.04283755,0.001977714,0.1194133,0.01167257,0.470929],"study_design_scores_gemma":[0.00001934499,0.000141823,0.2209323,0.008049656,0.0002778472,0.0004291987,0.02011114,0.1155974,0.00205827,0.5368698,0.0951789,0.0003343412],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.261477,0.05803947,0.5738593,0.07234824,0.001099204,0.0003940514,0.00604581,0.0004157894,0.02632115],"genre_scores_gemma":[0.7883938,0.01783638,0.187089,0.002506959,0.0007425386,0.0006174434,0.001076578,0.0001389723,0.001598248],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02074121,"threshold_uncertainty_score":0.09796596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.12820718659677,"score_gpt":0.315111769786137,"score_spread":0.186904583189367,"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."}}