{"id":"W2900483577","doi":"10.1109/igarss.2018.8517852","title":"Relationships of Phenological and Inter-Annual Landscape Dynamics with Biodiversity in Farmlands","year":2018,"lang":"en","type":"article","venue":"","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Normalized Difference Vegetation Index; Biodiversity; Phenology; Growing season; Vegetation (pathology); Butterfly; Environmental science; Ecology; Geography; Physical geography; Climate change; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002485498,0.00008104806,0.00008616787,0.000427703,0.0002279881,0.0004798783,0.0001943185,0.0001513098,0.0009778133],"category_scores_gemma":[0.001048558,0.0001314751,0.0001293023,0.0004373065,0.0003069311,0.0002889649,0.0002362356,0.0001067759,0.00008512347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001560879,"about_ca_system_score_gemma":0.0004654064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2017069,"about_ca_topic_score_gemma":0.5062537,"domain_scores_codex":[0.9999149,0.00001538816,0.000005275804,0.00002226265,0.00001475946,0.00002739743],"domain_scores_gemma":[0.9992595,0.0002260351,0.0002384331,0.00003920283,0.00008949046,0.0001472708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003475587,0.000009589054,0.9976153,0.000004720777,0.00001814095,0.00002807512,0.0001405007,0.0004575223,0.0006950079,0.00002175179,0.0000299377,0.0009446956],"study_design_scores_gemma":[3.475172e-7,0.000004587728,0.99955,5.6525e-7,0.000001795896,0.00000688295,0.00005309344,0.0003347764,0.00001716721,0.000006750163,0.00002331316,5.21905e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997416,0.00002180992,0.00002318722,0.000006396791,1.857408e-7,8.131305e-7,0.00006935165,9.406347e-7,0.0001357605],"genre_scores_gemma":[0.9997219,0.00001797601,0.00002980236,0.000001942215,4.259942e-7,0.000001426116,0.00008380204,5.644227e-7,0.0001420365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2017069,"threshold_uncertainty_score":0.4010656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01117639877976225,"score_gpt":0.2044861148237437,"score_spread":0.1933097160439814,"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."}}