{"id":"W7132869674","doi":"","title":"Description and prediction of vegetation recovery on inactive forest roads in Northern Ontario","year":2023,"lang":"en","type":"dissertation","venue":"TSpace","topic":"Science and Climate Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vegetation (pathology); Work (physics); Hydrology (agriculture); Geographic information system","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":[0.0001445784,0.0002069706,0.0002228432,0.0006967149,0.0007136039,0.001073224,0.0006704921,0.0003764286,0.003377977],"category_scores_gemma":[0.0008544135,0.0001672317,0.0003804564,0.001117482,0.0001977437,0.000281136,0.0002739619,0.0002418945,0.0009322446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004172417,"about_ca_system_score_gemma":0.004580317,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8999888,"about_ca_topic_score_gemma":0.951791,"domain_scores_codex":[0.9998735,0.000007834914,0.000006362297,0.00003511111,0.000036886,0.00004033248],"domain_scores_gemma":[0.9996704,0.00005496826,0.00003503073,0.00002281063,0.0001590667,0.00005776924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003373528,0.0001226633,0.7938159,0.0002226666,0.00009797689,0.0004164671,0.0008668694,0.1379031,0.003240059,0.001431415,0.01344392,0.04810158],"study_design_scores_gemma":[0.0000275486,0.00003673173,0.7439344,0.00005820137,0.00003875266,0.00005367747,0.001362168,0.2418969,0.001114691,0.0004724477,0.0109754,0.0000290081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9674304,0.0001578844,0.001682219,0.0001470618,0.00001300541,0.00007384829,0.02029972,0.0002127629,0.009983087],"genre_scores_gemma":[0.9771608,0.0001293175,0.00174031,0.00001086326,0.00000473551,0.00003731362,0.01309251,0.00004113637,0.007782981],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1000112,"threshold_uncertainty_score":0.2012004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02477217812515036,"score_gpt":0.2732889362830417,"score_spread":0.2485167581578914,"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."}}