{"id":"W2221351895","doi":"","title":"It's about time: purpose, methods, and challenges of temporal analyses of multiple data streams","year":2010,"lang":"en","type":"article","venue":"International Conference of Learning Sciences","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Simon Fraser University","funders":"","keywords":"Computer science; Data stream mining; Data science; Coding (social sciences); Perspective (graphical); STREAMS; Data mining; Set (abstract data type); Data set; Data collection; Face (sociological concept); Machine learning; 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":[0.1768907,0.002030943,0.00343152,0.008501185,0.004411468,0.02267958,0.006624719,0.004562533,0.002227896],"category_scores_gemma":[0.367268,0.002127448,0.002880762,0.01391267,0.01824564,0.03916357,0.009186924,0.01266311,0.0010015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004623106,"about_ca_system_score_gemma":0.01206102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007511139,"about_ca_topic_score_gemma":0.004978859,"domain_scores_codex":[0.8543568,0.1160499,0.006618612,0.00790118,0.01382674,0.001246759],"domain_scores_gemma":[0.4427019,0.4660794,0.02072768,0.0405747,0.02612633,0.00379002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004832298,0.0002895749,0.01903457,0.002570924,0.0005800594,0.0004693479,0.03385744,0.0105797,0.001969669,0.4999372,0.01371765,0.4165107],"study_design_scores_gemma":[0.00007122914,0.0001043865,0.00398156,0.001478464,0.0001402334,0.0004626791,0.01265356,0.0564497,0.00195763,0.8847213,0.03771897,0.0002602935],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007298028,0.006372985,0.9534906,0.02627511,0.001018619,0.0006482519,0.0003078694,0.0003402037,0.004248343],"genre_scores_gemma":[0.1563984,0.007411337,0.824377,0.002849541,0.002264448,0.003797678,0.0002934296,0.000646007,0.001962174],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1768907,"threshold_uncertainty_score":0.9354985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1920179239580016,"score_gpt":0.4452308270013598,"score_spread":0.2532129030433582,"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."}}