{"id":"W4241733194","doi":"10.4095/300965","title":"Presence of Humans in Forests - Kilometres of Roads","year":2010,"lang":"en","type":"report","venue":"","topic":"Ecology, Conservation, and Geographical Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kilometer; Geography; Ecology; Forestry; Biology; Transport engineering; Engineering","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":[0.0001751415,0.0001551955,0.0001519695,0.001057402,0.0007258091,0.0007215916,0.0003639509,0.0002363809,0.005768997],"category_scores_gemma":[0.0008239885,0.000152353,0.0001674618,0.001799396,0.000326787,0.0004629862,0.0006005178,0.0002502836,0.001015542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005914887,"about_ca_system_score_gemma":0.0009018729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2393766,"about_ca_topic_score_gemma":0.5330275,"domain_scores_codex":[0.9995787,0.00006615416,0.00003019987,0.00006105535,0.0001433798,0.0001206056],"domain_scores_gemma":[0.9990061,0.00008163109,0.0003335143,0.0000619116,0.0002932195,0.0002236714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002841835,0.00003545732,0.982139,0.00007573329,0.000030872,0.0001511688,0.0007591067,0.00008625933,0.0002552233,0.0001449062,0.004171515,0.01212233],"study_design_scores_gemma":[0.000001154949,0.0000155946,0.9942937,0.00003171855,0.000009830484,0.000290639,0.001690248,0.00002794956,0.0000419806,0.00002626893,0.003567601,0.000003224053],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9426549,0.001220637,0.0001683486,0.0002856069,0.00003787928,0.00005997131,0.02179464,0.00002892836,0.03374899],"genre_scores_gemma":[0.9842763,0.001485305,0.0002101514,0.00007041747,0.00003398565,0.000027172,0.006384968,0.000005109564,0.007506543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2393766,"threshold_uncertainty_score":0.4759666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02564547842584914,"score_gpt":0.2877440058174621,"score_spread":0.262098527391613,"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."}}