{"id":"W3196149083","doi":"","title":"Lumber trade war slaughtering US construction industry","year":2018,"lang":"en","type":"article","venue":"FOXBusiness","topic":"Global trade, sustainability, and social impact","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Business; Commerce; International trade; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002090721,0.0002349902,0.0002438748,0.0001343252,0.0004024568,0.000268696,0.0002280165,0.0003138481,0.0003894356],"category_scores_gemma":[0.0001773847,0.0002308298,0.00009241111,0.0008689337,0.0003722809,0.001436099,0.0001131558,0.0002761411,0.0001437394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000986735,"about_ca_system_score_gemma":0.00004814225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001579523,"about_ca_topic_score_gemma":0.0001223561,"domain_scores_codex":[0.9986311,0.00001386134,0.0002730518,0.0003279482,0.0002629842,0.0004910216],"domain_scores_gemma":[0.9992951,0.00001273166,0.0001496146,0.0002651036,0.0002482233,0.00002928129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002066366,0.0003830412,0.9297708,0.0008560292,0.0001395134,0.00007872342,0.001558118,0.0000547784,0.0006863037,0.02222345,0.01570616,0.02833645],"study_design_scores_gemma":[0.001275877,0.000027115,0.8304197,0.0001242483,0.0001775002,0.00002925874,0.005962919,0.0007097638,0.0002153514,0.01402582,0.1461197,0.0009127485],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9627314,0.00003023552,0.0001528783,0.001339235,0.002032012,0.0002240503,0.000005489509,0.0002544423,0.03323022],"genre_scores_gemma":[0.9928151,0.000002948722,0.0001023358,0.001334326,0.00557406,0.000007232165,0.00002061316,0.00003310597,0.0001102394],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1304136,"threshold_uncertainty_score":0.9412968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01923102936680243,"score_gpt":0.2543637373448941,"score_spread":0.2351327079780917,"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."}}