{"id":"W4400450585","doi":"10.31219/osf.io/dwcjv","title":"Hidden Markov Model: Tutorial","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Explainable Artificial Intelligence (XAI)","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Hidden Markov model; Markov model; Markov chain; Artificial intelligence; Machine learning","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":[0.001738927,0.002522527,0.001668189,0.002310786,0.0004725546,0.00189559,0.002386814,0.00274337,0.05585585],"category_scores_gemma":[0.005502908,0.001015688,0.00165425,0.003607055,0.0007893032,0.004526575,0.001426649,0.003865893,0.02757858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001283916,"about_ca_system_score_gemma":0.00136371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003053996,"about_ca_topic_score_gemma":0.002287131,"domain_scores_codex":[0.9988187,0.0004073549,0.0001194235,0.0002812493,0.0003063993,0.000066851],"domain_scores_gemma":[0.9975049,0.001775883,0.0001182552,0.0001962508,0.0003309047,0.00007380982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007562304,0.0001095074,0.0007873783,0.00431627,0.000242945,0.0004971828,0.0003446402,0.02370961,0.001842569,0.2349506,0.3506726,0.3824511],"study_design_scores_gemma":[0.00001237087,0.00004969967,0.0003928185,0.000655701,0.00005018979,0.0005227126,0.00003934816,0.02303069,0.0003548204,0.1563516,0.8184923,0.00004776882],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.001058286,0.2212156,0.6995569,0.004779201,0.008769622,0.0002674535,0.005519071,0.004782456,0.0540513],"genre_scores_gemma":[0.03191544,0.3456873,0.48782,0.007881725,0.02094696,0.00185445,0.02072091,0.004009113,0.07916404],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.05585585,"threshold_uncertainty_score":0.1868564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03586957649827612,"score_gpt":0.2963604752412013,"score_spread":0.2604908987429252,"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."}}