{"id":"W4399033088","doi":"10.1016/j.rbmo.2024.103996","title":"Using simulation to optimize IVF lab resources and meet physiological time constraints","year":2024,"lang":"en","type":"article","venue":"Reproductive BioMedicine Online","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Thomas Hospital","funders":"","keywords":"Computer science; Biochemical engineering; Environmental science; Engineering","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":[0.00105657,0.0006903227,0.0007981296,0.0006863824,0.0005207237,0.001315545,0.001011669,0.001432239,0.004066353],"category_scores_gemma":[0.005566558,0.0006152153,0.0006530832,0.0005917001,0.0004856057,0.0008450545,0.0009713661,0.0009538698,0.0002387991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001072183,"about_ca_system_score_gemma":0.002312109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0241149,"about_ca_topic_score_gemma":0.01488748,"domain_scores_codex":[0.9995087,0.0002701799,0.00002101098,0.00005966744,0.0000552902,0.00008515026],"domain_scores_gemma":[0.9955019,0.003673762,0.0002231202,0.0001186893,0.0002662346,0.0002162759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003308511,0.00002861997,0.0008661519,0.000007729578,0.0000105995,0.00001720207,0.00001171309,0.9972249,0.00008345429,0.0004395701,0.0001253612,0.001151519],"study_design_scores_gemma":[0.0000157051,0.0000176414,0.0001415197,0.000003111959,0.000005761629,0.000004208091,0.0000145693,0.9989769,0.00007264294,0.0005885282,0.0001564223,0.000003100291],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6145104,0.0005529748,0.3434915,0.002640634,0.0002663538,0.0003038813,0.001104892,0.001072844,0.03605656],"genre_scores_gemma":[0.979515,0.00009045209,0.01853751,0.0001040298,0.00002063391,0.0001036675,0.000222793,0.00004738648,0.001358533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0241149,"threshold_uncertainty_score":0.04794908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06783351824730675,"score_gpt":0.3936361021304468,"score_spread":0.32580258388314,"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."}}