{"id":"W2320871501","doi":"10.1139/x11-110","title":"Mechanisms and source distances for the input of large woody debris to forested streams in British Columbia, Canada","year":2011,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of British Columbia; Simon Fraser University; Ministry of Environment","funders":"Ministry of Forests, Lands and Natural Resource Operations; National Science Foundation","keywords":"Large woody debris; STREAMS; Debris; Channel (broadcasting); Hydrology (agriculture); Geology; Erosion; Sediment; Bank erosion; Geomorphology; Ecology; Oceanography; Habitat; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0004296815,0.0003252091,0.0002590948,0.00142509,0.0009806373,0.001621697,0.0004738304,0.000302056,0.001761329],"category_scores_gemma":[0.002125833,0.0003870536,0.0003062247,0.001025193,0.0005203323,0.0004062709,0.0008176827,0.0002914987,0.0001414768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007762961,"about_ca_system_score_gemma":0.005135702,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.782223,"about_ca_topic_score_gemma":0.8936858,"domain_scores_codex":[0.9997519,0.0000306028,0.00002233591,0.00005085287,0.0000743603,0.00007005913],"domain_scores_gemma":[0.9988727,0.0002913772,0.0002554707,0.00004327117,0.0003409389,0.0001963528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008151433,0.00005105996,0.9782216,0.00006577058,0.00006579227,0.0002242911,0.0005902562,0.004534205,0.001993887,0.0003953139,0.0003731199,0.01340312],"study_design_scores_gemma":[0.000008300044,0.00001286348,0.9947378,0.00001589498,0.00002505897,0.00004635441,0.0003832291,0.004079579,0.0002186648,0.0001852909,0.0002788199,0.000008226974],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981438,0.0001860273,0.0003055374,0.00006642262,0.000002140885,0.00001703826,0.0003194428,0.00002520034,0.0009344189],"genre_scores_gemma":[0.9987845,0.0001451053,0.0003217726,0.000009283728,0.00000158219,0.000006269261,0.0002715158,0.000005829111,0.0004542702],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.217777,"threshold_uncertainty_score":0.4381191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02054746027317865,"score_gpt":0.2437858749223326,"score_spread":0.223238414649154,"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."}}