{"id":"W3048896201","doi":"10.1007/s40471-020-00242-5","title":"Trajectory Modeling with Latent Groups: Potentials and Pitfalls","year":2020,"lang":"en","type":"article","venue":"Current Epidemiology Reports","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; Université Laval; Foothills Medical Centre; University of Calgary","funders":"Alberta Children's Hospital Research Institute; Alberta Innovates - Health Solutions","keywords":"Trajectory; Data science; Latent class model; Computer science; Field (mathematics); Psychology; Machine learning; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00100586,0.0002548332,0.000968814,0.00005623192,0.00006271138,0.000006009203,0.0000634133,0.0001017314,0.00006300275],"category_scores_gemma":[0.001852308,0.0001912955,0.0001232625,0.0001201277,0.0001692032,0.00009053735,0.00009311067,0.0003348529,0.00001792148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003201205,"about_ca_system_score_gemma":0.0001238255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000185387,"about_ca_topic_score_gemma":0.000002947886,"domain_scores_codex":[0.9974442,0.0002626284,0.0008936852,0.0008123107,0.0001646103,0.0004226258],"domain_scores_gemma":[0.9982788,0.0001828613,0.0003789284,0.0004592533,0.0001098542,0.0005903071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003401414,0.0001551529,0.9803912,0.0004441009,0.0002322915,0.001477731,0.0001810354,0.002839012,0.0004742219,0.0002029818,0.00557276,0.007689368],"study_design_scores_gemma":[0.004678516,0.001610699,0.7611411,0.00139247,0.00155921,0.007659378,0.0001766605,0.1871406,0.0001272445,0.00322046,0.02949764,0.00179604],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9544996,0.01429142,0.0268334,0.002811208,0.0004587356,0.0006012759,0.00002913081,0.0002764112,0.0001987981],"genre_scores_gemma":[0.9955398,0.0007580426,0.001420961,0.001590056,0.0003335579,0.00003472281,0.000278395,0.00003206964,0.00001234427],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2192501,"threshold_uncertainty_score":0.7800805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1049471048114064,"score_gpt":0.3349753570556964,"score_spread":0.23002825224429,"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."}}