{"id":"W2285008036","doi":"10.1145/2839509.2844655","title":"Computational Thinking as a Liberal Study","year":2016,"lang":"en","type":"article","venue":"","topic":"Teaching and Learning Programming","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Entertainment; Computational thinking; Data science; Management science; Computer security; Human–computer interaction; Artificial intelligence; Political science; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0004100466,0.00006309277,0.00006108791,0.00005032786,0.0001710186,0.000190949,0.0004554077,0.00001591802,0.00003311698],"category_scores_gemma":[0.00004761696,0.00003747961,0.00002741304,0.0001051167,0.000009844867,0.00027941,0.0001671951,0.00007859639,0.0002736808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001677896,"about_ca_system_score_gemma":0.00003063506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004213428,"about_ca_topic_score_gemma":0.000003038547,"domain_scores_codex":[0.9991755,0.00009673701,0.00009784147,0.0002233967,0.0002522794,0.0001542051],"domain_scores_gemma":[0.9995474,0.0001605002,0.00003070154,0.0001886075,0.00002610461,0.00004665698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000002117947,0.0001557439,0.02221345,9.021493e-7,0.00001739078,0.00001868209,0.006503415,0.0002997854,0.000008975567,0.1207167,0.0004682564,0.8495945],"study_design_scores_gemma":[0.009240453,0.004510601,0.3924695,0.0002720994,0.00003664656,0.0004110816,0.002285164,0.05333083,0.000143985,0.2745596,0.2603359,0.002404161],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.139342,0.000006783426,0.8557175,0.002355863,0.000142077,0.00007534499,3.888166e-8,0.0005971895,0.001763142],"genre_scores_gemma":[0.8306324,7.464304e-8,0.1662104,0.0002548173,0.00003402367,0.000004142222,1.215375e-7,0.000003720949,0.002860203],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8471904,"threshold_uncertainty_score":0.3517703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01468571364323043,"score_gpt":0.2749992473198669,"score_spread":0.2603135336766365,"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."}}