{"id":"W6913096006","doi":"10.5683/sp3/8sdfld","title":"Getting the word out on APIs: The ups and downs of offering support for a new technology","year":2018,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Word (group theory); Join (topology); Information technology; Word processing; The Internet","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003557485,0.002829476,0.001439953,0.004039669,0.002197185,0.004436281,0.00401513,0.002624688,0.01493195],"category_scores_gemma":[0.01921277,0.0007868632,0.00169158,0.006048073,0.001207752,0.006987594,0.005191616,0.004179437,0.05249895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002889371,"about_ca_system_score_gemma":0.002425682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0507977,"about_ca_topic_score_gemma":0.1491326,"domain_scores_codex":[0.9955004,0.0009891407,0.0004233703,0.0009150634,0.001569862,0.0006022076],"domain_scores_gemma":[0.9922964,0.001499122,0.0005472337,0.002831987,0.001889827,0.0009354234],"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":[0.00009714594,0.00003035987,0.001332028,0.0002269028,0.00002021316,0.00002819563,0.00007659962,0.0001445979,0.0001387638,0.0009698233,0.9913845,0.005550914],"study_design_scores_gemma":[0.00008632543,0.00002712581,0.005545684,0.0002207292,0.00002248393,0.0001598514,0.0003034809,0.001008263,0.0007524819,0.002475679,0.9893544,0.00004349791],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00303555,0.0008407526,0.001378986,0.002464816,0.000621707,0.000063537,0.9762267,0.006560076,0.008807957],"genre_scores_gemma":[0.00234498,0.00018405,0.001660363,0.000342763,0.00005119498,0.00007881384,0.9925857,0.0004399981,0.002312115],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0507977,"threshold_uncertainty_score":0.1010041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02807989199772368,"score_gpt":0.294169003589022,"score_spread":0.2660891115912983,"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."}}