{"id":"W3122478233","doi":"","title":"Using Previously Reported Cropland Acreage in Data Collection","year":2009,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Respondent; Geography; Agriculture; Quarter (Canadian coin); Livestock; Agricultural experiment station; West virginia; Agricultural economics; Forestry; Archaeology; Political science","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":[0.005072088,0.001071138,0.0006280506,0.006130594,0.001109546,0.001411045,0.001267398,0.0003263284,0.01194083],"category_scores_gemma":[0.01140207,0.0004270318,0.0008716891,0.01057428,0.0003829348,0.00127774,0.001183127,0.0009910563,0.005900009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001519282,"about_ca_system_score_gemma":0.002138211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02891571,"about_ca_topic_score_gemma":0.06368133,"domain_scores_codex":[0.9940584,0.001191829,0.001058528,0.001452022,0.001795293,0.0004439168],"domain_scores_gemma":[0.9843124,0.002098898,0.003962927,0.002371749,0.00682096,0.0004332039],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003280875,0.001315705,0.7722657,0.001319758,0.0003045144,0.0004444293,0.003105685,0.003997755,0.004269475,0.002488105,0.06294983,0.147211],"study_design_scores_gemma":[0.00004138649,0.0004265838,0.8277873,0.0002004547,0.00007411792,0.0001293531,0.002165054,0.002365144,0.003040627,0.0006557613,0.1630447,0.00006947028],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4987848,0.0009665666,0.04292817,0.0003065724,0.0006770193,0.01497504,0.3184921,0.001492762,0.121377],"genre_scores_gemma":[0.4444781,0.002032239,0.09233069,0.0004192,0.0003051741,0.02641848,0.3980281,0.0004604001,0.03552759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02891571,"threshold_uncertainty_score":0.05749482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1521916776047344,"score_gpt":0.3590293093142713,"score_spread":0.206837631709537,"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."}}