{"id":"W2132515156","doi":"10.24908/pceea.v0i0.3858","title":"\"RUGPLOT\" VISUALIZATION FOR PRELIMINARY DESIGN","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Ontario Centres of Excellence","keywords":"Computer science; Plot (graphics); Visualization; Graph; Software; Class (philosophy); Scatter plot; Software engineering; Systems engineering; Data science; Data mining; Engineering; Theoretical computer science; Artificial intelligence; Programming language; Mathematics; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.004709982,0.001851881,0.0009551215,0.003251281,0.0009988581,0.003294406,0.001870297,0.001091907,0.1258389],"category_scores_gemma":[0.02313262,0.0007828205,0.001234232,0.002606353,0.0006307521,0.002908669,0.002938939,0.002532178,0.02043545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000766219,"about_ca_system_score_gemma":0.002230949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002377173,"about_ca_topic_score_gemma":0.002563782,"domain_scores_codex":[0.9974548,0.001200147,0.0002116283,0.000247511,0.0007470515,0.0001387682],"domain_scores_gemma":[0.9879829,0.00706812,0.0005783752,0.001959226,0.002148342,0.0002629798],"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":[0.0005534764,0.0002161004,0.001496553,0.002168354,0.0001394353,0.0004310382,0.002943598,0.008097926,0.009558993,0.04585919,0.5534565,0.3750789],"study_design_scores_gemma":[0.0002308753,0.0001773048,0.00248256,0.0007230639,0.0000695134,0.0003701557,0.0005368424,0.0550215,0.01151426,0.04585011,0.8828655,0.0001583752],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002936188,0.0003529736,0.8069784,0.001043493,0.0006250542,0.000714726,0.01060954,0.1521316,0.02460814],"genre_scores_gemma":[0.03925411,0.000435771,0.9073362,0.0005931942,0.0001881402,0.003135615,0.009652612,0.0270243,0.0123801],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1258389,"threshold_uncertainty_score":0.420973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02497704491680681,"score_gpt":0.2417239451980511,"score_spread":0.2167469002812443,"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."}}