{"id":"W7097242021","doi":"","title":"and Price Statistics","year":2001,"lang":"en","type":"article","venue":"","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Production (economics); Government (linguistics); Boom; Industrial production; Panel data; Wood industry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001650488,0.001132803,0.0008057365,0.01025409,0.000892941,0.003689081,0.001708873,0.0009338608,0.2195592],"category_scores_gemma":[0.01251692,0.0004456764,0.0006976214,0.02076979,0.0002776172,0.003206417,0.0009832995,0.001782868,0.1868145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001755758,"about_ca_system_score_gemma":0.002783277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02157241,"about_ca_topic_score_gemma":0.01481169,"domain_scores_codex":[0.9960651,0.0002721689,0.0005291431,0.0004526786,0.002424633,0.0002562903],"domain_scores_gemma":[0.9913014,0.001277078,0.0007924656,0.0007687373,0.005548446,0.0003119013],"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":[0.00005025772,0.00004057879,0.002182656,0.0001780184,0.00001160774,0.00003611494,0.00005540971,0.0002375145,0.00008054817,0.006661141,0.9381809,0.05228526],"study_design_scores_gemma":[0.000008106513,0.00001996096,0.004891563,0.00007816948,0.000005570298,0.00007095021,0.00007833284,0.0002003738,0.00007852462,0.001342738,0.9932106,0.00001503368],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.003215283,0.003948036,0.003027294,0.002935229,0.00307657,0.0003543282,0.7006396,0.002039227,0.2807645],"genre_scores_gemma":[0.0139928,0.00691764,0.003673428,0.001146862,0.001387351,0.0005096102,0.7151623,0.0008541273,0.2563559],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7804408,"threshold_uncertainty_score":0.7344987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008012769681756871,"score_gpt":0.2252340757068421,"score_spread":0.2172213060250852,"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."}}