{"id":"W3111165480","doi":"10.33262/concienciadigital.v3i4.1.1476","title":"Estimación de parámetros para imágenes digitales, usando clasificadores K-NN y Tesseract","year":2020,"lang":"es","type":"article","venue":"ConcienciaDigital","topic":"Knowledge Societies in the 21st Century","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Physics; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008717554,0.0007599732,0.0008798984,0.0001173245,0.001127598,0.001923464,0.002018041,0.0005536188,0.0004253938],"category_scores_gemma":[0.00588607,0.0007777411,0.0006850512,0.001804268,0.003583816,0.001952515,0.0006131598,0.0007449005,0.001772932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006361795,"about_ca_system_score_gemma":0.002038534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008936816,"about_ca_topic_score_gemma":0.00001666381,"domain_scores_codex":[0.9940939,0.000361495,0.0008788666,0.001269024,0.001392548,0.002004171],"domain_scores_gemma":[0.995755,0.001206534,0.0004813499,0.0005618709,0.0004053722,0.001589924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000508818,0.001357652,0.6562148,0.0006898808,0.0006910269,0.0005236535,0.08710577,0.0001514777,0.007092102,0.01545341,0.04899597,0.1812154],"study_design_scores_gemma":[0.005401481,0.002063187,0.1724066,0.0008824413,0.0007820284,0.0001002722,0.05942532,0.006498379,0.01221668,0.003154534,0.7314503,0.005618758],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8887925,0.00653804,0.0007272603,0.001586964,0.001314272,0.000805909,0.0004227948,0.0005495074,0.09926277],"genre_scores_gemma":[0.9927042,0.001350252,0.0003285337,0.001632601,0.002251838,0.00004638625,0.00004789959,0.0001039911,0.001534364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6824543,"threshold_uncertainty_score":0.9994674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05195510435184754,"score_gpt":0.3398060280841969,"score_spread":0.2878509237323493,"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."}}