{"id":"W4387464144","doi":"10.1071/mf23100","title":"Numerical modelling for ecologically successful spawning-site restoration in Chin-sha River, China","year":2023,"lang":"en","type":"article","venue":"Marine and Freshwater Research","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Restoration ecology; Habitat; Context (archaeology); Channel (broadcasting); Fishery; Ecology; Environmental science; Geography; Biology; Computer science","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":[0.0004414323,0.0006249457,0.0006798115,0.0007589021,0.001045901,0.001274918,0.001246473,0.001430363,0.002736598],"category_scores_gemma":[0.001088011,0.0004742142,0.001062907,0.0007441513,0.0009078978,0.0006398832,0.0009016035,0.0005179331,0.0001764794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002288357,"about_ca_system_score_gemma":0.003435533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1622888,"about_ca_topic_score_gemma":0.08316965,"domain_scores_codex":[0.9998202,0.00004569305,0.00001244758,0.00003597413,0.00002534287,0.00006036783],"domain_scores_gemma":[0.99966,0.0001282749,0.00005290856,0.00001938763,0.00008717176,0.00005228487],"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":[0.00001872696,0.00001781832,0.005036881,0.00001841625,0.00001195904,0.00008898495,0.00002997315,0.9925939,0.0003656554,0.0006126762,0.0001260631,0.001078976],"study_design_scores_gemma":[0.000007560817,0.00001039993,0.001466311,0.000003238232,0.000006838633,0.000007735246,0.00003204584,0.9980733,0.00006141753,0.0002070874,0.000118819,0.000005213619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9583672,0.0002890997,0.02786483,0.0004543611,0.0000506032,0.00009026796,0.0007062876,0.0001845508,0.01199282],"genre_scores_gemma":[0.9951571,0.0001129084,0.002279895,0.00001870053,0.000006241377,0.00006356291,0.0001643063,0.00001994456,0.002177337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1622888,"threshold_uncertainty_score":0.3226884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04684032377520993,"score_gpt":0.3054309134015561,"score_spread":0.2585905896263462,"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."}}