{"id":"W6958302844","doi":"10.6084/m9.figshare.14623174.v1","title":"Additional file 1 of Diversity of plant assemblages dampens the variability of the growing season phenology in wetland landscapes","year":2021,"lang":"en","type":"article","venue":"Open MIND","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Université Laval","funders":"","keywords":"Phenology; Edaphic; Growing season; Table (database); Wetland; Spatial variability; Diversity (politics)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001398416,0.0009443698,0.0009996397,0.001981133,0.0008788723,0.00134578,0.001854319,0.0009270055,0.8539101],"category_scores_gemma":[0.01600976,0.000441734,0.0006521325,0.003476802,0.0002454203,0.001613335,0.001009736,0.000693266,0.1392954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008028758,"about_ca_system_score_gemma":0.001225186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01250017,"about_ca_topic_score_gemma":0.01980436,"domain_scores_codex":[0.999481,0.0001033166,0.0000766618,0.0001466471,0.0001127562,0.00007967363],"domain_scores_gemma":[0.9881123,0.009099803,0.0005395619,0.0006280541,0.001357059,0.0002631774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002340548,0.0001569379,0.005413685,0.002809056,0.00005249838,0.00006943422,0.0001743022,0.0007741976,0.0001960007,0.0007741482,0.9770229,0.01232284],"study_design_scores_gemma":[0.003189744,0.0003154344,0.07773045,0.002793422,0.0002137979,0.0005015506,0.001442126,0.004572473,0.001246784,0.009397086,0.8983968,0.0002002216],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0003890674,0.00001053288,0.0003436567,0.0000512635,0.00001374705,0.00007159549,0.9982287,0.000192723,0.0006986033],"genre_scores_gemma":[0.01577368,0.00009423304,0.007317051,0.0003243247,0.00007525239,0.003261412,0.962728,0.0009575676,0.009468521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8539101,"threshold_uncertainty_score":0.2083794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01557976879514109,"score_gpt":0.2153701760739906,"score_spread":0.1997904072788495,"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."}}