{"id":"W4287244254","doi":"10.48550/arxiv.2104.00634","title":"Security and Machine Learning Adoption in IoT: A Preliminary Study of\\n IoT Developer Discussions","year":2021,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Internet of Things; Computer science; World Wide Web; Computer security; Resource (disambiguation); Computer network","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":[0.009256781,0.0003478586,0.0004018831,0.002551586,0.003643369,0.002798309,0.0006477924,0.00126516,0.003176852],"category_scores_gemma":[0.04099321,0.0003452938,0.0003248292,0.002104282,0.002239344,0.004941433,0.003236991,0.001877172,0.0006406491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002185,"about_ca_system_score_gemma":0.00134831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01067506,"about_ca_topic_score_gemma":0.01471546,"domain_scores_codex":[0.9939453,0.003302269,0.0004283305,0.0006128814,0.001121566,0.0005896491],"domain_scores_gemma":[0.933307,0.0507515,0.007105934,0.001335321,0.005370928,0.002129401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001924364,0.0003874594,0.15237,0.0003274275,0.00002018782,0.0005987678,0.8181054,0.000100001,0.002130785,0.001958425,0.003931215,0.01987789],"study_design_scores_gemma":[0.00003147161,0.0001712554,0.2141721,0.0002996982,0.00002809332,0.0002310044,0.7472146,0.001702699,0.00131413,0.001434031,0.0333268,0.00007400447],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900141,0.0001775721,0.0006881348,0.001749422,0.00002945594,0.00007504326,0.0002699316,0.00002151256,0.006974795],"genre_scores_gemma":[0.9950478,0.0002393948,0.0006881797,0.000765707,0.00005341081,0.0002264345,0.0003362749,0.00003680479,0.002605893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01067506,"threshold_uncertainty_score":0.04895514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0560549084329281,"score_gpt":0.1883316075603427,"score_spread":0.1322766991274146,"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."}}