{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002401357,0.001157516,0.0009901123,0.0004737403,0.0003459298,0.001110099,0.0009579813,0.0008389461,0.0003881342],"category_scores_gemma":[0.0009148459,0.001453591,0.0005718013,0.0008438112,0.0001460024,0.0004133352,0.0003670628,0.002109968,0.000331819],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007204951,"about_ca_system_score_gemma":0.00140047,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006682744,"about_ca_topic_score_gemma":0.00003386801,"domain_scores_codex":[0.9939161,0.0004806204,0.001020132,0.00102267,0.0005077155,0.003052778],"domain_scores_gemma":[0.9967146,0.0007157258,0.0001540009,0.001115576,0.00008084491,0.001219241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001255695,0.0004763592,0.03004801,0.01078949,0.002428725,0.01034746,0.03813964,0.1875806,0.6743585,0.01557243,0.01014477,0.01998833],"study_design_scores_gemma":[0.0009827835,0.0004564138,0.01326504,0.005973987,0.001076355,0.004350629,0.002126078,0.8170912,0.08273518,0.0001771761,0.06912591,0.00263919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8167116,0.04945041,0.1268566,0.0002429445,0.000725652,0.001045314,0.00008383358,0.002852041,0.002031628],"genre_scores_gemma":[0.9543161,0.001697599,0.04027489,0.0002113406,0.0009275338,0.000252415,0.00003925687,0.0006879813,0.001592889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6295106,"threshold_uncertainty_score":0.9999269,"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."}}