{"id":"W3128834497","doi":"10.1007/978-3-030-67209-6_2","title":"Low Cost and User Friendly IoT Laboratory: Design and Implementation","year":2021,"lang":"en","type":"book-chapter","venue":"Advances in intelligent systems and computing","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Cloud computing; Internet of Things; Computer science; Curriculum; Engineering management; Software engineering; Software; Multidisciplinary approach; Project-based learning; Experiential learning; Engineering education; Automation; Multimedia; Engineering; World Wide Web; Operating system; Mathematics education","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007400194,0.0004121733,0.0005601639,0.0002133385,0.0002899593,0.0005174977,0.0002748603,0.0001695771,0.000002471369],"category_scores_gemma":[0.00001890321,0.0004186253,0.00003844354,0.000124594,0.00009211001,0.0003233654,0.0005477286,0.0003394485,0.000004025529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008960481,"about_ca_system_score_gemma":0.00008348739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000357438,"about_ca_topic_score_gemma":0.00001226683,"domain_scores_codex":[0.9976466,0.0001063413,0.0006956333,0.0008678883,0.0002696191,0.0004139432],"domain_scores_gemma":[0.9985864,0.0004159896,0.0003981055,0.0003099788,0.0001547752,0.0001348151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001322782,0.00002911097,0.002125924,0.001118867,0.00009481578,0.0001874415,0.00246426,0.00274543,0.0000394143,0.228975,0.001020818,0.7611857],"study_design_scores_gemma":[0.0008715272,0.0003309664,0.0002105293,0.005363629,0.00004986234,0.0002472467,0.0009382538,0.196925,0.0007175061,0.003126832,0.7894135,0.001805189],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001682797,0.04637418,0.9421921,0.00004670165,0.005829557,0.0008274676,0.000002488828,0.00009636662,0.002948378],"genre_scores_gemma":[0.5017938,0.06795561,0.373553,0.001962427,0.01933559,0.0002556016,0.0002082616,0.0008584705,0.03407722],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7883927,"threshold_uncertainty_score":0.9998266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01986143910906441,"score_gpt":0.2868513274698127,"score_spread":0.2669898883607483,"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."}}