{"id":"W3193067369","doi":"10.1002/ecs2.3699","title":"Links between fluctuations in sockeye salmon abundance and riparian forest productivity identified by remote sensing","year":2021,"lang":"en","type":"article","venue":"Ecosphere","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Pacific Salmon Foundation","keywords":"Riparian zone; Oncorhynchus; Abundance (ecology); Spawn (biology); Ecology; STREAMS; Environmental science; Fishery; Productivity; Geography; Biology; Habitat; Fish <Actinopterygii>","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":[0.0004326682,0.0001884989,0.0001457868,0.00073475,0.00021383,0.0006399936,0.0001878012,0.0001664159,0.001016923],"category_scores_gemma":[0.001179755,0.0001534948,0.0002174055,0.0008450646,0.0002080009,0.0002386002,0.0002924248,0.0001861942,0.0001103078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005808641,"about_ca_system_score_gemma":0.0004470281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2024924,"about_ca_topic_score_gemma":0.3918364,"domain_scores_codex":[0.9998223,0.0000321374,0.00001679081,0.00005843635,0.00002762645,0.00004270364],"domain_scores_gemma":[0.9989265,0.000264717,0.0003767335,0.000066058,0.0002111583,0.0001548682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001765041,0.000007908583,0.9984101,0.000003084603,0.00004195099,0.0000125545,0.00002083626,0.0003236666,0.0003429999,0.000008944198,0.00006185626,0.0007483787],"study_design_scores_gemma":[7.264101e-7,0.000004660435,0.9987438,0.000001487679,0.000006872376,0.000007867302,0.00005747617,0.001098976,0.00002544088,0.000005915569,0.00004525981,0.000001430867],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993045,0.0000324245,0.00008091771,0.00001187506,0.000001862072,0.000001957674,0.0003787614,0.000004941862,0.0001825978],"genre_scores_gemma":[0.9994968,0.00001657703,0.00005160722,0.000005325625,0.000001769456,0.000001671071,0.0003499555,9.864033e-7,0.00007534314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2024924,"threshold_uncertainty_score":0.4026276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008882068170810331,"score_gpt":0.2221192228728822,"score_spread":0.2132371547020719,"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."}}