{"id":"W2032206377","doi":"10.1007/s11355-010-0103-6","title":"Landscape scale assessment of stream channel and riparian habitat restoration needs","year":2010,"lang":"en","type":"article","venue":"Landscape and Ecological Engineering","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Ministry of Environment; Great Lakes Protection Fund; Ministry of Natural Resources","keywords":"Riparian zone; Sinuosity; Stream restoration; Environmental science; Channel (broadcasting); Hydrology (agriculture); Floodplain; Restoration ecology; STREAMS; Environmental resource management; Land cover; Habitat; Riparian buffer; Geography; Land use; Ecology; Computer science; Cartography; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001596454,0.00009463772,0.0001437845,0.0000354127,0.00006257819,0.00001221743,0.00005765826,0.0001242937,0.0004733173],"category_scores_gemma":[0.00001491649,0.00007302408,0.00001644643,0.00009712137,0.00005759756,0.0001253545,0.0000405572,0.000164094,0.000003714128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003499618,"about_ca_system_score_gemma":0.000003475344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006346714,"about_ca_topic_score_gemma":0.0001394579,"domain_scores_codex":[0.9994764,0.000006685789,0.0001311691,0.0001489303,0.00007816641,0.0001586046],"domain_scores_gemma":[0.9997627,0.00004984864,0.00002890777,0.00007059186,0.000003959443,0.00008395567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000104155,0.00008200291,0.9812621,0.00002738637,0.000009373314,0.000004499221,0.0001910843,0.006518252,0.01110495,0.0002590402,0.00007216573,0.0004586923],"study_design_scores_gemma":[0.0003398334,0.0001687529,0.9379128,0.000004546487,0.00001592678,0.000008915808,0.00004837022,0.0602695,0.0003554275,0.00009178747,0.0006730699,0.0001110703],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964629,0.00003667568,0.0004613408,0.000155197,0.00009013275,0.00007325792,0.000002938736,0.00003459177,0.002682985],"genre_scores_gemma":[0.9989679,0.00005005177,0.0008486829,0.00004274449,0.00003034406,0.00001218315,0.00001075692,0.000004746285,0.00003253703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05375125,"threshold_uncertainty_score":0.5182492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004721425611923651,"score_gpt":0.1965930179421869,"score_spread":0.1918715923302633,"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."}}