{"id":"W4417293150","doi":"10.63282/3117-5481/aijcst-v3i5p102","title":"How Citizen Developers Changed the Game","year":2021,"lang":"","type":"article","venue":"American International Journal of Computer Science and Technology","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsemi (Canada)","funders":"","keywords":"Task (project management); Benchmarking; Deliverable; Modular design; Reinforcement learning; Action (physics); Autonomy; Software deployment; Intelligent agent","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":[0.007952656,0.0006048696,0.0003400626,0.001232924,0.00964644,0.01225349,0.002437163,0.00444366,0.02464451],"category_scores_gemma":[0.029705,0.0006332322,0.0006135728,0.001341927,0.008866858,0.01234724,0.007715204,0.006585337,0.008535767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007196343,"about_ca_system_score_gemma":0.007403711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02652985,"about_ca_topic_score_gemma":0.04165628,"domain_scores_codex":[0.9891939,0.005986123,0.000283662,0.001317605,0.001708858,0.001509861],"domain_scores_gemma":[0.99138,0.002406261,0.0004520773,0.001106147,0.002273758,0.002381652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000171436,0.0003060975,0.01267588,0.0002069169,0.00003380723,0.002446554,0.1035176,0.0007001632,0.001295979,0.3098516,0.4073287,0.1614654],"study_design_scores_gemma":[0.00001976169,0.00003788852,0.001006512,0.0001192136,0.00000902285,0.0002702491,0.0314021,0.00060363,0.0004044634,0.01398787,0.9521078,0.00003149032],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1405237,0.001885758,0.02421249,0.1790137,0.005998248,0.000304217,0.000392664,0.001701731,0.6459675],"genre_scores_gemma":[0.5921557,0.001299057,0.01352622,0.02257266,0.0002580093,0.0001953209,0.0004627831,0.00207387,0.3674564],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02652985,"threshold_uncertainty_score":0.08244413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205522832968115,"score_gpt":0.2542565824229696,"score_spread":0.2422013540932885,"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."}}