{"id":"W2028544104","doi":"10.1109/educon.2013.6530204","title":"Classroom response systems in higher education: Meeting user needs with NetClick","year":2013,"lang":"en","type":"article","venue":"","topic":"Innovative Teaching Methods","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Premise; Variety (cybernetics); Computer science; Context (archaeology); Factor (programming language); Multimedia; Engineering education; Human–computer interaction; Engineering management; Engineering; Artificial intelligence","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":[0.007617896,0.0004667255,0.0004932772,0.0008308965,0.001021415,0.003020497,0.002304783,0.001047087,0.0131806],"category_scores_gemma":[0.02614418,0.000363007,0.0003657159,0.0007161666,0.0005950221,0.005305241,0.002872441,0.001347525,0.002910227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001096684,"about_ca_system_score_gemma":0.001981108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002732627,"about_ca_topic_score_gemma":0.009895694,"domain_scores_codex":[0.9962077,0.001426164,0.0002715535,0.0003809627,0.001446865,0.0002667719],"domain_scores_gemma":[0.974683,0.01753699,0.0009178797,0.002570776,0.002889919,0.001401465],"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":[0.001452333,0.001294974,0.0239543,0.001276805,0.00003807403,0.00128461,0.01418719,0.001314173,0.03818483,0.006086805,0.02504801,0.8858781],"study_design_scores_gemma":[0.0009947929,0.007297678,0.09243922,0.002236882,0.0004751958,0.009865375,0.02947082,0.05950088,0.1127968,0.01189914,0.6721841,0.0008391188],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7138231,0.001611804,0.1854596,0.0144336,0.0002571507,0.001230766,0.0005108531,0.03361099,0.04906215],"genre_scores_gemma":[0.7368093,0.0009783059,0.2246594,0.002487119,0.0001664496,0.0005570353,0.0009117649,0.002564721,0.03086596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0131806,"threshold_uncertainty_score":0.04409355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06098499462902345,"score_gpt":0.3608678176248186,"score_spread":0.2998828229957952,"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."}}