{"id":"W4245969999","doi":"10.1002/ajh.25052","title":"ISSUE INFORMATION – TABLE OF CONTENTS","year":2018,"lang":"en","type":"paratext","venue":"American Journal of Hematology","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Table (database); Citation; Information retrieval; Computer science; Table of contents; World Wide Web; Database","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007132275,0.001430375,0.001564666,0.002983328,0.001398928,0.007738199,0.001648668,0.001623152,0.9303699],"category_scores_gemma":[0.006782379,0.0005984791,0.0006563801,0.004152456,0.0004801455,0.00418344,0.001510764,0.002275391,0.9172901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001459145,"about_ca_system_score_gemma":0.002238895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004174042,"about_ca_topic_score_gemma":0.004890757,"domain_scores_codex":[0.9992657,0.0000743211,0.00006210151,0.0001399694,0.0003608425,0.00009714158],"domain_scores_gemma":[0.9953991,0.0006163747,0.0002456637,0.000412393,0.002203375,0.00112311],"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":[0.00001134389,0.0000157471,0.00004842181,0.00009976623,0.000001159448,0.000007760231,0.000004740767,0.00002947504,0.00004803555,0.0005107332,0.9833218,0.01590111],"study_design_scores_gemma":[0.00001466191,0.0000129219,0.000365108,0.0001417301,0.000001320581,0.00002084201,0.0000159804,0.00004168524,0.00005658087,0.0005254782,0.9987991,0.000004726794],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001732548,0.0007807518,0.0004645572,0.001966426,0.009541385,0.0003083247,0.03779034,0.001922757,0.9470521],"genre_scores_gemma":[0.001119807,0.0008921967,0.0003352061,0.001226022,0.002784381,0.0001292767,0.02032331,0.001025597,0.9721642],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.06963009,"threshold_uncertainty_score":0.09931886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01643390759841842,"score_gpt":0.2487697075030919,"score_spread":0.2323357999046735,"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."}}