{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009652458,0.0009534749,0.0007232805,0.0009830161,0.0003376978,0.001163579,0.0008457114,0.001086653,0.003765035],"category_scores_gemma":[0.004035735,0.0003720708,0.0007096792,0.0008850895,0.0004467945,0.001179921,0.0004638631,0.0006529961,0.001220015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006951138,"about_ca_system_score_gemma":0.0005712381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003124195,"about_ca_topic_score_gemma":0.002862888,"domain_scores_codex":[0.9993175,0.00008732474,0.00004709281,0.0001826448,0.0003228732,0.00004258024],"domain_scores_gemma":[0.9982498,0.0007996506,0.0001890861,0.0001644392,0.0005521916,0.00004476079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001278364,0.0001782617,0.009365393,0.001121948,0.0001881347,0.000205175,0.0005077026,0.173797,0.1642718,0.001843709,0.001836337,0.6454063],"study_design_scores_gemma":[0.00004015687,0.0008023812,0.01788843,0.0001787657,0.0001442837,0.0004598359,0.0004006579,0.7941356,0.1747836,0.001748948,0.009305716,0.0001116792],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1663276,0.001778979,0.8251296,0.0001618324,0.0001861823,0.000114377,0.0003255825,0.00180259,0.004173196],"genre_scores_gemma":[0.5999875,0.001329019,0.3898466,0.0001112328,0.00004730123,0.0001991828,0.0004915743,0.0001975811,0.007790055],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003765035,"threshold_uncertainty_score":0.01259536,"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."}}