{"id":"W4224122686","doi":"10.1111/rec.13703","title":"Plains rough fescue grassland restoration using natural regeneration after pipeline disturbances","year":2022,"lang":"en","type":"article","venue":"Restoration Ecology","topic":"Rangeland and Wildlife Management","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Natural Resources Limited","keywords":"Species evenness; Species richness; Environmental science; Grassland; Ecological succession; Topsoil; Plant community; Revegetation; Restoration ecology; Threatened species; Ecology; Biology; Habitat; Soil science; Soil water","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0002884642,0.0001682775,0.0001137769,0.0002107791,0.0002968549,0.0002239559,0.0002484008,0.00009867386,0.0004641509],"category_scores_gemma":[0.000328746,0.00005568947,0.0001559742,0.00009567522,0.000215323,0.0001894156,0.0002566015,0.000103632,0.00006263131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007221479,"about_ca_system_score_gemma":0.0007255473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02167427,"about_ca_topic_score_gemma":0.1197914,"domain_scores_codex":[0.9998986,0.00001609231,0.000004729899,0.0000255061,0.00002004127,0.00003508548],"domain_scores_gemma":[0.9998552,0.00001342268,0.00005261976,0.00001478016,0.00002557307,0.0000384446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00421113,0.007966124,0.3798111,0.0004322017,0.0002991696,0.00188852,0.002492517,0.007593734,0.3517447,0.0006996572,0.001015124,0.2418461],"study_design_scores_gemma":[0.0000509093,0.005423131,0.9790815,0.00002133879,0.00003297582,0.0003386473,0.0006489874,0.002350587,0.009428511,0.0001241165,0.002486386,0.00001282718],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995301,0.00004147298,0.0001614584,0.000004228288,0.000001112038,0.00001381043,0.00001534644,0.000005437789,0.0002270609],"genre_scores_gemma":[0.9989614,0.00004453878,0.0004158631,0.000004860817,0.000001209434,0.00001161405,0.00007777611,9.170244e-7,0.0004818213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02167427,"threshold_uncertainty_score":0.04309624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070787107331641,"score_gpt":0.2289477690191665,"score_spread":0.2182398979458501,"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."}}