{"id":"W4394273123","doi":"10.6084/m9.figshare.1287365","title":"Effect of Roadside Vegetation Cutting on Moose Browsing","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Plant Pathogens and Fungal Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vegetation (pathology); Geography; Environmental science; Physical geography; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001025862,0.0006655818,0.0008272897,0.001376475,0.0004524411,0.001061973,0.001120121,0.0006374806,0.03297495],"category_scores_gemma":[0.005399974,0.0003101513,0.001100168,0.002414107,0.0002123799,0.0007119926,0.0009959603,0.000914212,0.01298136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001286534,"about_ca_system_score_gemma":0.001333705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06666493,"about_ca_topic_score_gemma":0.13154,"domain_scores_codex":[0.9992933,0.0001233322,0.0000663576,0.0002847802,0.0001213845,0.0001107594],"domain_scores_gemma":[0.9978835,0.0007852658,0.0003397781,0.0004276558,0.0003975774,0.0001662496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005838238,0.00005966078,0.05689918,0.001397261,0.0004385674,0.00005793892,0.0001405257,0.001107038,0.0005266655,0.0006576074,0.9285576,0.009574084],"study_design_scores_gemma":[0.000471356,0.00008591077,0.3728933,0.0007147235,0.0003707728,0.0001997501,0.0003148688,0.001347157,0.001329673,0.00108739,0.6210814,0.0001037687],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002574773,0.00007268963,0.00006364564,0.00007762108,0.00001799968,0.000006705028,0.9963031,0.0001848477,0.0006986521],"genre_scores_gemma":[0.009371432,0.00008331083,0.0004987614,0.00008682475,0.000007804158,0.0000665659,0.9876797,0.0001649683,0.002040718],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06666493,"threshold_uncertainty_score":0.1325538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01748602740195429,"score_gpt":0.276216835330535,"score_spread":0.2587308079285808,"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."}}