{"id":"W4285286727","doi":"10.1007/978-3-031-09593-1_8","title":"Toward a Trip Planner Adapted to Older Adults Context: Mobilaînés Project","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Planner; Computer science; Socialization; Context (archaeology); Public transport; Human–computer interaction; Transport engineering; Artificial intelligence; Psychology; Engineering; Social psychology","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":[0.0002316022,0.0003524407,0.0003415172,0.0007994073,0.0001120375,0.00009057662,0.0006279261,0.0001635598,0.0003807282],"category_scores_gemma":[0.0000371999,0.0003527905,0.00008330111,0.0007192562,0.0001256268,0.0001521006,0.00007975345,0.0006538215,0.00002351284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002469895,"about_ca_system_score_gemma":0.0002706676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005846511,"about_ca_topic_score_gemma":0.0003638775,"domain_scores_codex":[0.9979926,0.000008714808,0.0004446535,0.0006586335,0.0005236149,0.0003717884],"domain_scores_gemma":[0.9990933,0.0001163161,0.00005644863,0.0004788171,0.0001411971,0.0001139231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000512803,0.00005271493,0.00004071259,0.0001616208,0.00003978742,0.00008108852,0.01232324,0.4159158,0.00009704413,0.007291963,0.0006199488,0.5633247],"study_design_scores_gemma":[0.004592952,0.001154588,0.003100291,0.002644955,0.0001023734,0.0001558758,0.00004834174,0.5204576,0.002269577,0.005971218,0.4542736,0.005228673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001819325,0.0002217709,0.9898486,0.0005028938,0.001930155,0.001496689,0.0001505938,0.0004878255,0.003542119],"genre_scores_gemma":[0.977056,0.00001708578,0.01982212,0.00219378,0.0002085095,0.0001718484,0.0001211449,0.00007309723,0.0003364006],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9752367,"threshold_uncertainty_score":0.9998924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02146200136001295,"score_gpt":0.2409976628710362,"score_spread":0.2195356615110233,"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."}}