{"id":"W2782366106","doi":"","title":"RENEGOCIACIÓN DEL TLC PARA BENEFICIAR A MÉXICO","year":2017,"lang":"es","type":"article","venue":"","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Economics; Philosophy","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":[0.0007856697,0.0002643933,0.0002245728,0.001416099,0.001328467,0.002247389,0.0005244814,0.0005263787,0.01040034],"category_scores_gemma":[0.001368835,0.0001289753,0.0003479911,0.002582554,0.000720358,0.001160769,0.001090509,0.0006364757,0.0004190904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006293712,"about_ca_system_score_gemma":0.004136055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1357177,"about_ca_topic_score_gemma":0.2139932,"domain_scores_codex":[0.9996643,0.00005267649,0.00001295014,0.00008393021,0.000067705,0.0001184121],"domain_scores_gemma":[0.999046,0.0001598893,0.0003683543,0.00007300036,0.0002641847,0.00008857253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009540043,0.0002023646,0.4350125,0.002343538,0.0002421915,0.002739475,0.01444532,0.002224224,0.01280763,0.05590349,0.02715776,0.4459675],"study_design_scores_gemma":[0.00002646232,0.0002058086,0.6709774,0.0007246569,0.0003115988,0.0005016348,0.01102083,0.0006572671,0.004661996,0.00200764,0.3088678,0.00003689814],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8996655,0.01453376,0.002320099,0.005518381,0.0001366191,0.00006438515,0.002310778,0.0001684786,0.07528199],"genre_scores_gemma":[0.9595383,0.01097523,0.002335704,0.0003018052,0.00008144923,0.00005196465,0.0009591645,0.00002973038,0.0257266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1357177,"threshold_uncertainty_score":0.2698554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03520578410826362,"score_gpt":0.2645529231027292,"score_spread":0.2293471389944656,"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."}}