{"id":"W2608216981","doi":"","title":"Evaluation of interannual variations in primary productivity by a simple vegetation model","year":2016,"lang":"en","type":"article","venue":"Japan Geoscience Union","topic":"Forest ecology and management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Humber Polytechnic","funders":"","keywords":"Primary productivity; Vegetation (pathology); Primary (astronomy); Simple (philosophy); Productivity; Environmental science; Climatology; Primary production; Physical geography; Geology; Ecology; Geography; Ecosystem; Biology; Medicine; Economics","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":[0.0006180427,0.0006473394,0.0008131206,0.000402035,0.0005233418,0.0004593269,0.0007329492,0.0007554477,0.0007900369],"category_scores_gemma":[0.001817729,0.0003726153,0.0007227093,0.0004560922,0.0002917787,0.0007161833,0.0003355505,0.0003542717,0.00007293038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008063383,"about_ca_system_score_gemma":0.0008723863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0328975,"about_ca_topic_score_gemma":0.0149626,"domain_scores_codex":[0.9998147,0.00006482432,0.00001248837,0.00004653375,0.00002921251,0.00003228175],"domain_scores_gemma":[0.9990578,0.0005945758,0.00006292186,0.00007097864,0.000143473,0.00007020003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001116901,0.00008227079,0.003556334,0.00002024716,0.00004755523,0.00003457698,0.0000126534,0.9905778,0.002619909,0.0002915793,0.00010627,0.002539066],"study_design_scores_gemma":[0.00001476172,0.00001695276,0.001019646,4.196436e-7,0.00001046968,0.000002817393,0.000002769254,0.9986342,0.0002280289,0.00004909009,0.00001751724,0.000003372322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9830942,0.00007378322,0.01507486,0.00006856717,0.00003306339,0.00001918525,0.0002018273,0.0001978905,0.001236592],"genre_scores_gemma":[0.9973747,0.00002084033,0.002278735,0.000007390805,0.000006578981,0.00001184099,0.0001091549,0.00002393797,0.0001668721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0328975,"threshold_uncertainty_score":0.06541204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01174620657210314,"score_gpt":0.2415089383452993,"score_spread":0.2297627317731961,"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."}}