{"id":"W7020959681","doi":"","title":"Modelo para armar : Itinerarios y ámbitos disidentes del Partido Comunista en la formación de uno de los grupos fundadores de las Fuerzas Armadas Revolucionarias (1960-1967)","year":2012,"lang":"es","type":"article","venue":"Orientación y Sociedad","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Yield (engineering); Work (physics); Value (mathematics); Quarter (Canadian coin)","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":["metaepi_narrow","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003516075,0.001107805,0.0009482715,0.0002861909,0.001359349,0.001355973,0.002839644,0.0007840938,0.0002249148],"category_scores_gemma":[0.000744193,0.001182718,0.0007008133,0.001032523,0.0009391086,0.003062179,0.001479764,0.001551854,0.0006114772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001517649,"about_ca_system_score_gemma":0.001354344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001279928,"about_ca_topic_score_gemma":0.0001832699,"domain_scores_codex":[0.9907364,0.001605198,0.001499591,0.001208657,0.001403671,0.003546528],"domain_scores_gemma":[0.9939692,0.001866359,0.0007465426,0.001710913,0.000368879,0.001338112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002972053,0.002405828,0.5218392,0.0005669581,0.000608754,0.0002515287,0.0920681,0.004203388,0.01139213,0.3190271,0.02478323,0.02255659],"study_design_scores_gemma":[0.001913887,0.0007609981,0.03314135,0.001411175,0.0009371004,0.000909519,0.02047342,0.5320826,0.1239124,0.05778404,0.2216425,0.005031062],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6896631,0.003380697,0.2989284,0.002180141,0.001674676,0.000919951,0.0001882011,0.0005067181,0.002558243],"genre_scores_gemma":[0.972818,0.001021701,0.02018165,0.002047622,0.001804627,0.0002768074,0.00005148508,0.0001593998,0.001638675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5278792,"threshold_uncertainty_score":0.9999408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03040712131394685,"score_gpt":0.3269165991019672,"score_spread":0.2965094777880204,"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."}}