{"id":"W2888408547","doi":"10.1177/0049124118782550","title":"Analyzing Heaped Counts Versus Longitudinal Presence/Absence Data in Joint Zero-inflated Discrete Regression Models","year":2018,"lang":"en","type":"article","venue":"Sociological Methods & Research","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Count data; Statistics; Outcome (game theory); Event (particle physics); Regression analysis; Event data; Econometrics; Mathematics; Rounding; Psychology; Computer science; Covariate","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01305727,0.0001044225,0.0002298096,0.0001380965,0.0007396097,0.000109617,0.0008966164,0.0002273992,0.002950714],"category_scores_gemma":[0.003990226,0.00007558599,0.00008261456,0.0006082889,0.00169996,0.0003080581,0.0007820885,0.0007125792,0.0002072162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001648366,"about_ca_system_score_gemma":0.0001317153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002542859,"about_ca_topic_score_gemma":0.0003588178,"domain_scores_codex":[0.9939933,0.003950579,0.00030035,0.0005448639,0.000562757,0.000648106],"domain_scores_gemma":[0.9975461,0.001406854,0.00006392527,0.000537503,0.0002902355,0.0001553255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002023883,0.001232382,0.1028655,0.0001812022,0.000412793,0.0002223998,0.03976082,0.00007898571,0.02104401,0.2167147,0.1146269,0.5008364],"study_design_scores_gemma":[0.003430462,0.002223542,0.1110594,0.001500197,0.00008120243,0.000004456895,0.02823258,0.1016349,0.00141701,0.6676124,0.0810478,0.001756088],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6023011,0.002447773,0.1965743,0.007690695,0.00225652,0.001423832,0.0001059437,0.000269847,0.18693],"genre_scores_gemma":[0.979512,0.0003710111,0.01839431,0.00001383814,0.0003633667,0.0000217012,0.00001997429,0.000008187769,0.001295652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4990803,"threshold_uncertainty_score":0.9979607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6965302466042542,"score_gpt":0.6410708432010603,"score_spread":0.05545940340319389,"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."}}