{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005611864,0.0010859,0.0009308543,0.001373103,0.001213903,0.003583252,0.002158399,0.001456367,0.007362437],"category_scores_gemma":[0.02066348,0.001025039,0.003305403,0.001302151,0.004611787,0.007630332,0.005194888,0.006825371,0.001652681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002402511,"about_ca_system_score_gemma":0.00245383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002093273,"about_ca_topic_score_gemma":0.003022481,"domain_scores_codex":[0.9958975,0.001694306,0.000230855,0.0007809112,0.001164686,0.0002317541],"domain_scores_gemma":[0.9936931,0.004059707,0.000251328,0.001004577,0.0007315145,0.0002598278],"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":[0.00001821396,0.00001808588,0.0001879333,0.00005951234,0.0000211745,0.00003449553,0.0001834535,0.01410065,0.0004966753,0.9671673,0.0009089251,0.01680361],"study_design_scores_gemma":[0.000005427867,0.00000671067,0.00003580319,0.00001907865,0.000008361175,0.00001746175,0.00002187262,0.06643213,0.000415487,0.9296507,0.003381052,0.000005804002],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002616721,0.00009967113,0.9927689,0.0006795166,0.0000337674,0.00003125819,0.00007594521,0.0002382703,0.003456037],"genre_scores_gemma":[0.1456655,0.0006314112,0.8447126,0.0009084797,0.0002634786,0.0002860971,0.0003833949,0.000506616,0.006642562],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007362437,"threshold_uncertainty_score":0.02967876,"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."}}