{"id":"W2511054836","doi":"10.1642/auk-16-92.1","title":"Trends, costs, benefits, challenges, and prognoses for supplementary materials","year":2016,"lang":"en","type":"article","venue":"The Auk","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Vetting; Reliability (semiconductor); Value (mathematics); Production (economics); Volume (thermodynamics); Computer science; Economics; Microeconomics","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":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.06366984,0.0009932668,0.001355723,0.01718626,0.001720283,0.0110682,0.002923079,0.003147477,0.1575001],"category_scores_gemma":[0.4719021,0.0007982369,0.002710777,0.02778029,0.00175227,0.01290201,0.003929481,0.003640858,0.02644529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005663299,"about_ca_system_score_gemma":0.009738422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002200685,"about_ca_topic_score_gemma":0.002897427,"domain_scores_codex":[0.9396402,0.03068255,0.008686563,0.002813646,0.01670584,0.001471214],"domain_scores_gemma":[0.3887558,0.4340796,0.05576935,0.02953964,0.08044058,0.011415],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001724309,0.0001453067,0.03145865,0.008271036,0.0003792256,0.0005647849,0.0003522008,0.001748277,0.000405552,0.03698902,0.4235122,0.4944496],"study_design_scores_gemma":[0.0005744747,0.0007339104,0.06354182,0.02893376,0.001334661,0.004000997,0.002344682,0.0118383,0.002498407,0.1182811,0.7654545,0.0004633223],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06749989,0.1138232,0.05454955,0.4074229,0.04206982,0.002423845,0.1829282,0.007462546,0.1218201],"genre_scores_gemma":[0.537197,0.07402632,0.1268902,0.03368008,0.02739807,0.00676257,0.1450827,0.0050246,0.04393849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9828137,"threshold_uncertainty_score":0.5268904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6499792727979707,"score_gpt":0.5435429268533936,"score_spread":0.1064363459445772,"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."}}