{"id":"W2611970523","doi":"","title":"SIMACT : a 3D open source smart home simulator for activity recognition with open database and visual editor","year":2012,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Computer science; Java; Field (mathematics); Set (abstract data type); Open source; Home automation; Human–computer interaction; Database; Software; Operating system","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001332915,0.0002682562,0.0004162413,0.0001179141,0.000356572,0.001511424,0.001086134,0.00009081696,0.00007849075],"category_scores_gemma":[0.0001382059,0.0002225882,0.00004428754,0.0002973982,0.00005969839,0.009685181,0.00206549,0.0001543992,0.0001075002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007521211,"about_ca_system_score_gemma":0.0001562035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007791585,"about_ca_topic_score_gemma":0.0003044752,"domain_scores_codex":[0.9980385,0.0002125837,0.0002410922,0.0006848526,0.0003151091,0.0005078089],"domain_scores_gemma":[0.9977345,0.0009292943,0.0002203419,0.0005181846,0.0002333721,0.0003643407],"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":[0.0009588103,0.001491085,0.0106522,0.0001625225,0.0002231803,0.000005017946,0.0009026258,0.000003980466,0.003256828,0.0001424551,0.01590437,0.9662969],"study_design_scores_gemma":[0.02627875,0.004251707,0.02732464,0.0009375408,0.000332216,0.000457582,0.001074482,0.3303746,0.03675316,0.0006435596,0.5662145,0.005357292],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1840158,0.00001973795,0.809997,0.0003938503,0.001331513,0.002767526,0.0001107901,0.0001897264,0.001174064],"genre_scores_gemma":[0.9788464,0.000001994315,0.01822813,0.0004482465,0.001289718,0.0004116154,0.00004431575,0.00003434808,0.0006952843],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9609396,"threshold_uncertainty_score":0.9995251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06173993797783035,"score_gpt":0.3279650969640978,"score_spread":0.2662251589862674,"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."}}