{"id":"W4375844197","doi":"10.1002/ecs2.4487","title":"Leaf phenology as an indicator of ecological integrity","year":2023,"lang":"en","type":"article","venue":"Ecosphere","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nova Scotia Department of Agriculture; Memorial University of Newfoundland; St. Francis Xavier University","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada; Northeastern States Research Cooperative; Compute Canada; Parks Canada; National Science Foundation","keywords":"Climate change; Environmental science; Ecosystem; Disturbance (geology); Context (archaeology); Phenology; Ecology; Frost (temperature); Plateau (mathematics); Duration (music); Atmospheric sciences; Geography; Biology; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0004343398,0.0001717167,0.0001616398,0.001387416,0.0001974913,0.0003867917,0.0001817647,0.0002004193,0.00145462],"category_scores_gemma":[0.001385843,0.00006879869,0.000122387,0.00081305,0.0001244621,0.0002827729,0.0003463142,0.0002254219,0.0002453601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003088435,"about_ca_system_score_gemma":0.00008732612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003769704,"about_ca_topic_score_gemma":0.007050002,"domain_scores_codex":[0.9998145,0.00004441102,0.00001282188,0.00005971644,0.00004359999,0.00002493279],"domain_scores_gemma":[0.9985227,0.0004379011,0.0004971754,0.00009825677,0.0002365046,0.0002074592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001476367,0.0000326151,0.9734677,0.00005603711,0.00005622517,0.00004118372,0.0001447106,0.002122189,0.01264547,0.00008760118,0.0003935699,0.01080503],"study_design_scores_gemma":[0.00000204103,0.00004621907,0.9947141,0.000004202541,0.00000623154,0.00006046965,0.00005895137,0.003706327,0.0008234334,0.0000552121,0.0005188931,0.000003945355],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938974,0.0001531848,0.00140338,0.00001809752,0.000006804768,0.00001420645,0.002819601,0.00007428387,0.001613128],"genre_scores_gemma":[0.9972574,0.00003021817,0.0009988224,0.000007956907,0.000006114087,0.000008884829,0.001448725,0.000007421684,0.0002345499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003769704,"threshold_uncertainty_score":0.007495522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05902373052907652,"score_gpt":0.2499785917533902,"score_spread":0.1909548612243137,"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."}}