{"id":"W2011772730","doi":"10.12962/j24068535.v10i1.a25","title":"OPTIMASI PENCAPAIAN TARGET PADA SIMULASI PERENCANAAN JALUR ROBOT BERGERAK DI LINGKUNGAN DINAMIS","year":2012,"lang":"id","type":"article","venue":"JUTI Jurnal Ilmiah Teknologi Informasi","topic":"Edcuational Technology Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Encana (Canada)","funders":"","keywords":"Physics","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","sts","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity"],"category_scores_codex":[0.00263919,0.001550005,0.001574859,0.001157494,0.001482512,0.0008711651,0.005078937,0.00190755,0.0001853745],"category_scores_gemma":[0.001402543,0.001454984,0.0007711349,0.002126263,0.00104815,0.00549542,0.002254874,0.003410009,0.001685575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00109943,"about_ca_system_score_gemma":0.001138378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001271623,"about_ca_topic_score_gemma":0.00008393217,"domain_scores_codex":[0.9897572,0.0004742081,0.00273335,0.001273467,0.001976329,0.003785487],"domain_scores_gemma":[0.992821,0.0006202225,0.001845391,0.002483428,0.0009346012,0.001295297],"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":[0.0003993573,0.003972739,0.4759999,0.001277078,0.003194481,0.0009347355,0.03136841,0.0183234,0.008325385,0.293256,0.02133387,0.1416146],"study_design_scores_gemma":[0.005032682,0.003220577,0.250717,0.0009610778,0.0005176621,0.003649183,0.005483525,0.1723526,0.02843297,0.001922881,0.5208786,0.006831304],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6783124,0.02112482,0.1245512,0.01938418,0.0428606,0.005801959,0.000177882,0.0063266,0.1014604],"genre_scores_gemma":[0.9635383,0.0004125723,0.02088881,0.0008220507,0.001538265,0.0001187504,0.00009633526,0.0001172035,0.0124677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4995447,"threshold_uncertainty_score":0.9998174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02712728739789394,"score_gpt":0.2648653774022922,"score_spread":0.2377380900043983,"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."}}