{"id":"W3034188862","doi":"10.1007/s10707-020-00408-9","title":"SWS: an unsupervised trajectory segmentation algorithm based on change detection with interpolation kernels","year":2020,"lang":"en","type":"article","venue":"GeoInformatica","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland; Dalhousie University","funders":"","keywords":"Trajectory; Segmentation; Computer science; Interpolation (computer graphics); Artificial intelligence; Sliding window protocol; Window (computing); Algorithm; Kernel (algebra); Pattern recognition (psychology); Computer vision; Mathematics; Motion (physics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001697964,0.0001581523,0.0001277556,0.0001410137,0.0001167958,0.0002999998,0.000429843,0.00003539048,0.00003693868],"category_scores_gemma":[0.000007820251,0.0001326847,0.00003408292,0.0004518642,0.00001901578,0.003862197,0.00006708025,0.0001041874,0.0001682764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003423475,"about_ca_system_score_gemma":0.00001947566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001954059,"about_ca_topic_score_gemma":0.000004913607,"domain_scores_codex":[0.9989048,0.0000429858,0.0002338651,0.0002287901,0.0003754072,0.0002141275],"domain_scores_gemma":[0.9993492,0.00002482991,0.0001074375,0.0003409144,0.00004344795,0.0001341074],"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":[0.00002953577,0.00006065229,0.00003667453,0.00005500468,0.00001685657,0.000005141874,0.004526102,0.0003706469,0.0001069846,0.0002912057,0.0001497632,0.9943514],"study_design_scores_gemma":[0.0007067239,0.0008407795,0.001054546,0.00002920982,0.00001132242,0.000001424649,0.0003697543,0.9948927,0.0008037318,0.00002477291,0.001078047,0.0001870604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002357269,0.000004263743,0.9950345,0.0005600023,0.0001374622,0.0004849358,0.00001256047,0.0003316517,0.0010774],"genre_scores_gemma":[0.603698,0.000006407844,0.3857726,0.009565277,0.0003884683,0.0001682723,0.0003479895,0.00002499857,0.00002798622],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.994522,"threshold_uncertainty_score":0.5410727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03146745409551396,"score_gpt":0.2314241320843101,"score_spread":0.1999566779887961,"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."}}