{"id":"W4366089786","doi":"10.3390/f14040812","title":"A Comparison of the International Competitiveness of Forest Products in Top Exporting Countries Using the Deviation Maximization Method with Increasing Uncertainty in Trading","year":2023,"lang":"en","type":"article","venue":"Forests","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Index (typography); International market; Business; China; Context (archaeology); Competitive advantage; Forest product; Sustainability; International trade; Agricultural economics; Economics; Environmental science; Forest management; Agroforestry; Geography; Marketing; Computer science; Ecology","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":[0.002852423,0.0006524763,0.0004898686,0.004073,0.0003618037,0.001843968,0.0003286927,0.0003320232,0.00082258],"category_scores_gemma":[0.005259066,0.0001246572,0.001010056,0.005379019,0.0005889398,0.001089281,0.001044945,0.0003864462,0.0001352951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008495253,"about_ca_system_score_gemma":0.0005367105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005119426,"about_ca_topic_score_gemma":0.003395254,"domain_scores_codex":[0.9986975,0.0004402502,0.0001182639,0.0001982975,0.0003895966,0.0001561982],"domain_scores_gemma":[0.997607,0.001147536,0.0004820099,0.0001943505,0.0004404919,0.0001285892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006121592,0.0001315037,0.8113619,0.0002535359,0.000616547,0.0007113372,0.00124797,0.08531456,0.003884166,0.009151646,0.001029843,0.08568484],"study_design_scores_gemma":[0.00002366589,0.0003152177,0.8464639,0.00007456031,0.0001751101,0.000453157,0.002872936,0.1365892,0.005026636,0.005143634,0.002756637,0.0001053427],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9830993,0.0003325341,0.009481361,0.00004559426,0.00001101294,0.00002923024,0.0004850266,0.00002923933,0.006486735],"genre_scores_gemma":[0.9950812,0.00009825505,0.003965872,0.000006092187,0.000005045213,0.0000198767,0.0005824251,0.000007031685,0.00023431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005119426,"threshold_uncertainty_score":0.01508522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04447809713447982,"score_gpt":0.3011603290629112,"score_spread":0.2566822319284314,"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."}}