{"id":"W4388764634","doi":"10.17760/d20618640","title":"Towards compositional probabilistic programming","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Computer science; Probabilistic logic; Artificial intelligence; Inference; Machine learning; Combinatory logic; Theoretical computer science; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001742605,0.0002125178,0.0002045889,0.000128702,0.0001226617,0.0003413061,0.0008015165,0.0001870311,0.00002883272],"category_scores_gemma":[0.00003465007,0.0001946167,0.00009781817,0.0003673949,0.00001628115,0.0001448105,0.00006871354,0.0002712431,0.0004104799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004594878,"about_ca_system_score_gemma":0.0003438321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008566939,"about_ca_topic_score_gemma":0.00009506464,"domain_scores_codex":[0.9985005,0.00003003331,0.0002673783,0.0005035158,0.0004185736,0.0002800591],"domain_scores_gemma":[0.9992089,0.00004487953,0.00009054911,0.0003529692,0.0002088624,0.00009381038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008250158,0.00009291177,0.000004659107,0.0002749467,0.00004362411,0.00003053634,0.0009340644,0.0001580821,0.0001508868,0.6084488,0.00314643,0.3867068],"study_design_scores_gemma":[0.0006885425,0.0005532382,0.005489949,0.001618747,0.0001247623,0.00006238474,0.0005987218,0.4319357,0.002302095,0.546499,0.006975502,0.003151312],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004371465,0.000124511,0.938392,0.0005784163,0.002689796,0.0005343994,0.000007427077,0.002508889,0.0507931],"genre_scores_gemma":[0.3901206,0.00005599115,0.5040816,0.0004722425,0.0006104349,0.0007056072,0.003097249,0.0001453448,0.1007109],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4343104,"threshold_uncertainty_score":0.7936238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03332265985880512,"score_gpt":0.3005301202912204,"score_spread":0.2672074604324153,"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."}}