{"id":"W2752681840","doi":"10.1111/trf.14305","title":"Determining the inventory impact of extended‐shelf‐life platelets with a network simulation model","year":2017,"lang":"en","type":"article","venue":"Transfusion","topic":"Blood donation and transfusion practices","field":"Business, Management and Accounting","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Blood Services; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Blood Services","keywords":"Shelf life; Off the shelf; Offset (computer science); Supply chain; Operations management; Software deployment; Platelet; Computer science; Business; Operations research; Medicine; Mathematics; Engineering; Internal medicine; Marketing; Biology; Food science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004121737,0.0001715476,0.0001914832,0.00008563229,0.0007942501,0.0002435421,0.0003324973,0.00007351441,0.000197596],"category_scores_gemma":[0.00007913557,0.0001052686,0.0001248105,0.0001270938,0.00009573971,0.001885534,0.00004181276,0.0001709756,0.00001868486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001123235,"about_ca_system_score_gemma":0.00005027929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004422283,"about_ca_topic_score_gemma":0.0003590633,"domain_scores_codex":[0.9989509,0.00001596257,0.0002597841,0.0002185388,0.0003439396,0.0002108873],"domain_scores_gemma":[0.9989268,0.00007511111,0.0003811355,0.0004098782,0.000186246,0.00002086739],"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":[0.001116184,0.0003758788,0.1798846,0.0001513208,0.0001720133,0.000008308958,0.0004527716,0.7318575,0.0005153118,0.004719954,0.0003869494,0.08035918],"study_design_scores_gemma":[0.001939297,0.00004549502,0.3162955,0.00008169428,0.0001495537,8.976744e-7,0.00003619114,0.6795598,0.00002368927,0.001008723,0.0006719257,0.0001871546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.982367,0.00004495205,0.006420833,0.0005197626,0.0001315795,0.0003440914,0.000001965149,0.00006407997,0.01010578],"genre_scores_gemma":[0.9990163,0.00005833111,0.0001520149,0.0003985272,0.0002802988,0.000009724166,0.000009590502,0.00002606078,0.0000491189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1364109,"threshold_uncertainty_score":0.610881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03998985263845271,"score_gpt":0.2920716560012299,"score_spread":0.2520818033627772,"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."}}