{"id":"W4404906360","doi":"10.1016/j.foreco.2024.122399","title":"Characterizing the Spectral-Temporal Signatures of Eastern Hemlock (Tsuga Canadensis) Using Sentinel-2 Satellite Images and Phenology Modelling","year":2024,"lang":"en","type":"article","venue":"Forest Ecology and Management","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service; University of Guelph","funders":"","keywords":"Tsuga; Phenology; Satellite; Environmental science; Remote sensing; Spectral signature; Ecology; Geography; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002935847,0.0002541911,0.0000991499,0.0004386797,0.0001054395,0.0002520327,0.0001529177,0.0001435128,0.0001452127],"category_scores_gemma":[0.0004460757,0.0001097414,0.0002521742,0.0002475704,0.0001152197,0.0002437406,0.0001338117,0.0001090471,0.00004758712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002840195,"about_ca_system_score_gemma":0.0002018927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01253194,"about_ca_topic_score_gemma":0.02648552,"domain_scores_codex":[0.9999417,0.00001242082,0.000002845551,0.00002234689,0.00001072982,0.000009941105],"domain_scores_gemma":[0.9998485,0.00005745403,0.00004323676,0.00001140162,0.00002077029,0.00001866776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002489502,0.0003088274,0.6433768,0.00007034931,0.0001380317,0.0001546448,0.0003532695,0.1851511,0.118602,0.0006332149,0.0003169501,0.05064591],"study_design_scores_gemma":[0.000006653114,0.00006411305,0.3552096,0.000003988137,0.000027084,0.00007683829,0.00009246315,0.6415032,0.002629553,0.0002229562,0.000150098,0.00001350861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956462,0.00002090669,0.00405889,0.000006873705,0.000001137874,0.00000481234,0.00007005371,0.00001882601,0.0001722727],"genre_scores_gemma":[0.9946665,0.00002720205,0.004981271,0.000003542202,0.000002103009,0.000007078425,0.0002123831,0.000004423655,0.00009561453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01253194,"threshold_uncertainty_score":0.02491796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009971108593966034,"score_gpt":0.2071892711273389,"score_spread":0.1972181625333729,"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."}}