{"id":"W6894146156","doi":"10.5281/zenodo.829886","title":"Proceedings Of The 8Th Workshop On Semantic Ambient Media Experiences (Same 2016): Smart Cities For Better Living With Hci And Ux - Seachi In Conjunction With The International Conference On Human-Computer Interaction (Chi)","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Conjunction (astronomy); Software deployment; Assisted living; Everyday life; Ambient intelligence; Social media; Smart environment; Panel discussion","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":[],"consensus_categories":[],"category_scores_codex":[0.006423463,0.001564437,0.00143334,0.0009525383,0.001891827,0.007337229,0.00193753,0.003089157,0.05864875],"category_scores_gemma":[0.005347748,0.0006256865,0.001452848,0.0009093829,0.002112118,0.008154536,0.01093692,0.005428663,0.01921059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001287511,"about_ca_system_score_gemma":0.003274098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002565704,"about_ca_topic_score_gemma":0.007024729,"domain_scores_codex":[0.9964603,0.001319012,0.0002288917,0.0004943794,0.001056412,0.0004410518],"domain_scores_gemma":[0.9960108,0.0007144813,0.0001137823,0.0004826009,0.001222267,0.001456189],"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":[0.0007783673,0.0007224361,0.001398601,0.001730358,0.00009202278,0.0005914141,0.01539963,0.0007245805,0.01333902,0.01251746,0.6902708,0.2624353],"study_design_scores_gemma":[0.00004947824,0.0002530915,0.002111007,0.0005416636,0.0000415991,0.0003630548,0.00372884,0.0008343511,0.002961814,0.004942678,0.9840919,0.00008053636],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.07787713,0.05638723,0.2753,0.05865877,0.1135396,0.002834131,0.00883279,0.01135469,0.3952156],"genre_scores_gemma":[0.1573717,0.03361657,0.1272344,0.008817716,0.01015319,0.003770215,0.02085809,0.005773426,0.6324047],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.05864875,"threshold_uncertainty_score":0.1961996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04157130946414832,"score_gpt":0.2411429166320552,"score_spread":0.1995716071679069,"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."}}