{"id":"W2128339142","doi":"10.1186/2193-1801-3-597","title":"An assessment of the predictors of the dynamics in arable production per capita index, arable production and permanent cropland and forest area based on structural equation models","year":2014,"lang":"en","type":"article","venue":"SpringerPlus","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Arable land; Index (typography); Production (economics); Per capita; Industrial production index; Environmental science; Structural equation modeling; Forestry; Geography; Statistics; Agriculture; Computer science; Environmental health; Mathematics; Medicine; Economics; Population","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":[0.00443547,0.001124749,0.0006109143,0.002465616,0.0004969481,0.001206697,0.000575198,0.000487775,0.002912248],"category_scores_gemma":[0.01073423,0.0004565141,0.001067776,0.002249465,0.0004114867,0.001232427,0.0008574095,0.001048404,0.0002950339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001035717,"about_ca_system_score_gemma":0.001889587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02259793,"about_ca_topic_score_gemma":0.02222347,"domain_scores_codex":[0.9981488,0.001262145,0.00006955161,0.0002333673,0.0001139285,0.0001721796],"domain_scores_gemma":[0.9888987,0.009092454,0.0009483838,0.0002461914,0.0005490463,0.0002652868],"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":[0.00008411767,0.0001224514,0.968875,0.00005067918,0.0003549151,0.0001812681,0.0005413477,0.01530314,0.0002364538,0.001686012,0.0004827688,0.01208183],"study_design_scores_gemma":[0.00004064314,0.0004732528,0.5416046,0.0001548767,0.000519688,0.0001811557,0.002208575,0.4492269,0.0005208666,0.003525108,0.001497946,0.00004631113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896917,0.0003196381,0.007497069,0.0005747824,0.00002477197,0.00004875427,0.0008172652,0.00005255731,0.0009734909],"genre_scores_gemma":[0.99624,0.0001786063,0.00255193,0.00001817124,0.00001360444,0.00003677552,0.0006889924,0.000005676141,0.0002662986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02259793,"threshold_uncertainty_score":0.04493278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070885105929328,"score_gpt":0.2159253260292329,"score_spread":0.2052164749699396,"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."}}