{"id":"W4243313770","doi":"10.21632/jpmi.1.1.230-240","title":"Pelatihan Pembuatan Robot Line Follower untuk Meningkatkan Pengetahuan Robotika pada Siswa SMK Negeri I Kramatwatu","year":2019,"lang":"en","type":"article","venue":"Jurnal Pemberdayaan Masyarakat Indonesia","topic":"Education and Character Development","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Robot; Robotics; Artificial intelligence; Enthusiasm; Service (business); Field (mathematics); Service robot; Engineering; Computer science; Human–computer interaction; Psychology; Mathematics; Social psychology","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001543875,0.0006204791,0.0007925431,0.0003977281,0.0009885054,0.0006031013,0.001033116,0.0003935301,0.004905554],"category_scores_gemma":[0.0001024922,0.0006109518,0.000386202,0.001025825,0.0002462016,0.0009677374,0.0002015208,0.0008782793,0.002294874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005855038,"about_ca_system_score_gemma":0.001114223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006038265,"about_ca_topic_score_gemma":0.001009013,"domain_scores_codex":[0.994577,0.0005302437,0.001039395,0.000917466,0.001614333,0.001321562],"domain_scores_gemma":[0.9971436,0.0002739876,0.0006122814,0.0007673937,0.000372839,0.0008299614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004678769,0.001488906,0.8521594,0.0002293852,0.0006010386,0.0002603765,0.08380704,0.0004758437,0.008264527,0.02372033,0.01574258,0.01278268],"study_design_scores_gemma":[0.003481837,0.0003321036,0.7844926,0.0003935589,0.000214995,0.0001198641,0.02324946,0.0002906985,0.00152942,0.001219501,0.1821085,0.002567415],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9271996,0.0002424466,0.0002167748,0.008066162,0.003720771,0.0009872471,0.00001107791,0.000302054,0.05925386],"genre_scores_gemma":[0.9663526,0.000133095,0.001262589,0.0009679225,0.001221985,0.00006631399,0.0001057813,0.00009862192,0.02979114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.166366,"threshold_uncertainty_score":0.9996342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929322008264833,"score_gpt":0.292193526665329,"score_spread":0.2729003065826807,"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."}}