{"id":"W4245141124","doi":"10.24124/2012/bpgub1545","title":"Forecasting future consumption of coniferous wood in India: a quantitative approach","year":2012,"lang":"en","type":"dissertation","venue":"","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Softwood; Gross domestic product; Agricultural economics; Economics; Consumption (sociology); Ordinary least squares; Econometrics; Engineering; Pulp and paper industry; Macroeconomics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002199213,0.0002677992,0.0004283694,0.0003817855,0.00005418927,0.00007007414,0.0001864094,0.0002718306,0.0001898769],"category_scores_gemma":[0.00002505919,0.0002496301,0.00009817883,0.0004154413,0.00002683929,0.0006014158,0.00003330248,0.0002659511,0.00005967659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002864915,"about_ca_system_score_gemma":0.00003038658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004190681,"about_ca_topic_score_gemma":0.0005090341,"domain_scores_codex":[0.9987907,0.00001594425,0.0003954825,0.0002718195,0.000241763,0.0002843182],"domain_scores_gemma":[0.9991698,0.00003816125,0.0004757929,0.0001253248,0.0001814179,0.000009485079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004401571,0.0006453974,0.2033849,0.006332639,0.0001537878,0.00001709775,0.0009374339,0.00003002465,0.0002635331,0.7825304,0.0001412052,0.005123413],"study_design_scores_gemma":[0.001276234,0.00002516812,0.970584,0.0007688097,0.0002156106,0.000004720508,0.02040992,0.0009630721,0.0001400613,0.001621299,0.003279282,0.0007118263],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.797258,0.0008673346,0.00006125946,0.00001229292,0.000732681,0.0004177337,0.000007573369,0.00004268042,0.2006005],"genre_scores_gemma":[0.9970635,0.00002528349,0.0004046099,0.00007533495,0.0005474031,0.00005306716,0.001259303,0.00003047149,0.0005410793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7809091,"threshold_uncertainty_score":0.9999956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0444790528593353,"score_gpt":0.2576230963469969,"score_spread":0.2131440434876616,"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."}}