{"id":"W4398520657","doi":"10.7910/dvn/db11yd","title":"PROSPERED Dataset: Paternity Leave","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research","keywords":"Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00137215,0.001667836,0.001459329,0.002247024,0.000851637,0.002084533,0.003086715,0.002375942,0.03328891],"category_scores_gemma":[0.007400383,0.0005815363,0.0014257,0.004161264,0.0004156493,0.001141254,0.00197197,0.002150171,0.04275155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001496085,"about_ca_system_score_gemma":0.001936721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03811541,"about_ca_topic_score_gemma":0.0686895,"domain_scores_codex":[0.9988769,0.000238078,0.0001460956,0.0003553292,0.0002265683,0.0001569476],"domain_scores_gemma":[0.9979086,0.0005340761,0.0003814299,0.0004712358,0.0004967613,0.0002079342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008244317,0.00003119197,0.003416733,0.0003555252,0.00004894137,0.00003830765,0.00003040554,0.0003809642,0.00005272852,0.0005940096,0.9925616,0.002407119],"study_design_scores_gemma":[0.0006987756,0.00004431612,0.02084325,0.0005852638,0.00008452617,0.0002480203,0.0001755061,0.001832448,0.0002780166,0.002873142,0.97227,0.00006673046],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003742153,0.0001043265,0.0000724152,0.0001208008,0.00002409363,0.000007720238,0.9987288,0.0001636833,0.000403935],"genre_scores_gemma":[0.0008129133,0.00006625478,0.0002637227,0.00008472589,0.0000131381,0.0000522241,0.9981647,0.00002976371,0.0005125717],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03811541,"threshold_uncertainty_score":0.1113626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03458317578973762,"score_gpt":0.3077230664053286,"score_spread":0.273139890615591,"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."}}