{"id":"W2785374143","doi":"10.1002/cjs.11795","title":"Clustering and semi‐supervised classification for clickstream data via mixture models","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canada Research Chairs; E.W.R. Steacie Memorial Fund","keywords":"Clickstream; Computer science; Mixture model; Cluster analysis; Machine learning; Artificial intelligence; Unsupervised learning; Data mining; Markov chain; Web page","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":[0.00620494,0.000989683,0.001741165,0.003608035,0.0007468089,0.002069122,0.00261565,0.001972414,0.001500923],"category_scores_gemma":[0.01515513,0.0006294714,0.001845134,0.002115723,0.001184593,0.002540019,0.001898552,0.002268472,0.001099966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001460814,"about_ca_system_score_gemma":0.001013256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008138981,"about_ca_topic_score_gemma":0.00802741,"domain_scores_codex":[0.9967077,0.001544454,0.0002378183,0.0007056228,0.0005435321,0.0002607736],"domain_scores_gemma":[0.9849195,0.01069902,0.001045883,0.001221229,0.00179938,0.0003149272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001011948,0.0006441018,0.01193728,0.000268103,0.0003276836,0.0001753581,0.0006136171,0.6412116,0.005332047,0.02055522,0.006223536,0.3116995],"study_design_scores_gemma":[0.000003814569,0.00001320139,0.0004510928,0.000005390631,0.00000471834,0.00001332064,0.00001299569,0.995653,0.0004277599,0.0032507,0.0001542884,0.000009707144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05453094,0.0003459419,0.9428034,0.0002316385,0.00005378887,0.0001141406,0.0003079562,0.001079717,0.0005326094],"genre_scores_gemma":[0.6537316,0.0002903137,0.3400277,0.0001283606,0.0001408298,0.0002780352,0.002430898,0.0002498578,0.002722458],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008138981,"threshold_uncertainty_score":0.03281522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09815003102868965,"score_gpt":0.2989763110525442,"score_spread":0.2008262800238546,"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."}}