{"id":"W6939557417","doi":"10.6084/m9.figshare.3527246.v1","title":"Appendix A. Tables showing climatic factors influencing the INDVI in May, the maximum NDVI increase and the average slope of NDVI between early May and early July in three study sites in Alberta, climatic factors influencing the INDVI in May, the maximum NDVI increase, and the average slope in NDVI between early May and early July, and correlation coefficients between climatic variables for the GPNP (Italy); and model selection procedures. Also included are figures showing interannual...","year":2016,"lang":"en","type":"dataset","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Normalized Difference Vegetation Index; Series (stratigraphy); Climate change; Time series; Hydrology (agriculture)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009941681,0.001069436,0.0008728294,0.002198029,0.0005618471,0.001247686,0.001729767,0.0006893868,0.1460497],"category_scores_gemma":[0.004303701,0.0006345789,0.0006624786,0.00492391,0.0002330921,0.0006291419,0.0007716255,0.0007542741,0.05583289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002201448,"about_ca_system_score_gemma":0.003583282,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1536509,"about_ca_topic_score_gemma":0.3125343,"domain_scores_codex":[0.9995632,0.00005729168,0.00006805956,0.0001197325,0.0001119263,0.00007989864],"domain_scores_gemma":[0.9965543,0.000935259,0.000374892,0.000467033,0.001393491,0.0002749685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000985859,0.00004720892,0.006322954,0.001081262,0.00005510441,0.00002718779,0.00003257523,0.001116087,0.000132906,0.0004475326,0.986335,0.004303553],"study_design_scores_gemma":[0.0008381295,0.0000304943,0.0519281,0.0005403867,0.00006387933,0.00005940856,0.0001273638,0.001019013,0.0003258697,0.001204843,0.9438216,0.00004085595],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009610266,0.00001028623,0.00003412903,0.000009047845,0.000003493765,0.00001216669,0.9995214,0.00005036305,0.0002631394],"genre_scores_gemma":[0.0008532969,0.00002478767,0.0004476037,0.00001906345,0.000003231681,0.0001368607,0.9976068,0.00003651821,0.0008718366],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8463491,"threshold_uncertainty_score":0.488585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02743441065052688,"score_gpt":0.2480075091363154,"score_spread":0.2205730984857885,"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."}}