{"id":"W4399625438","doi":"10.54751/revistafoco.v17n6-039","title":"DESAFIOS E OPORTUNIDADES NA ÁREA DE ENSINO DE ENGENHARIA, AUTOMAÇÃO E PÓS-COLHEITA DE GRÃOS: ESTUDO DE CASO DE MÁQUINA DE LIMPEZA","year":2024,"lang":"pt","type":"article","venue":"Revista Foco","topic":"Experimental Learning in Engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Humanities; Philosophy; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00116091,0.0003667346,0.0004401745,0.001293109,0.002734105,0.004144236,0.001018107,0.001202645,0.01005423],"category_scores_gemma":[0.004119253,0.0002494964,0.0005199416,0.002874885,0.002088613,0.00231056,0.001994034,0.000643424,0.001014054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003411649,"about_ca_system_score_gemma":0.00339886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03533016,"about_ca_topic_score_gemma":0.07669125,"domain_scores_codex":[0.9986381,0.0001932372,0.00006055844,0.000246599,0.0006297189,0.0002316934],"domain_scores_gemma":[0.9972612,0.00116141,0.0006357099,0.0001909514,0.0005655506,0.0001852138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006198633,0.0004173923,0.4760372,0.003512656,0.0001976039,0.007269534,0.1354686,0.003320772,0.07517853,0.02819538,0.005992997,0.2637894],"study_design_scores_gemma":[0.00001365127,0.0004320657,0.6478789,0.0005176367,0.0001251693,0.001712817,0.1803095,0.002219595,0.0203787,0.007582197,0.1386942,0.0001355586],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9403346,0.002877656,0.003725744,0.001049787,0.00004719554,0.0001335386,0.0003940998,0.00007756786,0.05135987],"genre_scores_gemma":[0.9765242,0.002565173,0.002583016,0.0001634224,0.00001422335,0.00007923751,0.0002303621,0.00003512936,0.01780518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03533016,"threshold_uncertainty_score":0.07024902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01416112211514961,"score_gpt":0.2750385858552671,"score_spread":0.2608774637401175,"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."}}