{"id":"W2762321513","doi":"10.1145/3132272.3132291","title":"Ambient Notifications with Shape Changing Circuits in Peripheral Locations","year":2017,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Task (project management); Distraction; Set (abstract data type); Embedding; Peripheral; Human–computer interaction; Electronic circuit; Artificial intelligence; Engineering; Electrical engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007827434,0.00007859233,0.0001007152,0.0003920517,0.0006462485,0.0009904538,0.0007931259,0.00002366991,0.001513389],"category_scores_gemma":[0.0001651007,0.0000550068,0.00003354782,0.0003398455,0.00007780624,0.001345097,0.0001035061,0.00006397729,0.0005506796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003825607,"about_ca_system_score_gemma":0.00003434318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005365555,"about_ca_topic_score_gemma":0.000612846,"domain_scores_codex":[0.9986737,0.00001779195,0.0002963323,0.0002109471,0.0006015639,0.0001996223],"domain_scores_gemma":[0.9988379,0.00004960076,0.0001724089,0.0007139374,0.0001660612,0.00006012832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001607766,0.0002626361,0.6450979,0.00000691052,0.00001730413,0.0000123257,0.009540151,0.001208601,0.0004634118,0.109447,0.007807916,0.2261198],"study_design_scores_gemma":[0.0003048639,0.00001652109,0.9530006,0.00001117733,0.000005409196,0.000001646324,0.00398974,0.02933875,0.00007523108,0.0003521805,0.01277023,0.0001336759],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9092236,0.000005478735,0.01185493,0.005142952,0.0001438681,0.0002521165,0.000005848509,0.00004221419,0.07332902],"genre_scores_gemma":[0.9784762,0.000001543325,0.0004462646,0.0003121597,0.00002391786,0.00004370606,0.000006100519,0.000004113741,0.02068604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3079028,"threshold_uncertainty_score":0.9993994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3083288576229203,"score_gpt":0.4332819472338779,"score_spread":0.1249530896109576,"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."}}