{"id":"W2764058170","doi":"10.1007/s11042-017-5246-0","title":"CASP: context-aware stress prediction system","year":2017,"lang":"en","type":"article","venue":"Multimedia Tools and Applications","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"CASP; Computer science; Context (archaeology); Stress (linguistics); Protein structure prediction","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":[0.0001853724,0.00015279,0.0002086842,0.00005818163,0.0009630166,0.0009087479,0.0007191521,0.00009770128,0.000007452597],"category_scores_gemma":[0.00004543618,0.0001477266,0.00005496826,0.00007270107,0.0001049657,0.001055312,0.0002517028,0.00013047,0.0001468217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005312172,"about_ca_system_score_gemma":0.00004460579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002368075,"about_ca_topic_score_gemma":0.0001214125,"domain_scores_codex":[0.9988008,0.00004312758,0.0002660474,0.0004756429,0.0002047721,0.0002095926],"domain_scores_gemma":[0.9980918,0.0001956272,0.0002586363,0.001116118,0.000169387,0.0001684782],"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":[0.000002836507,0.00007442986,0.009856787,0.00007671862,0.00003402216,0.000004845885,0.0003892002,0.000002799449,0.0003389492,0.008016645,0.000576966,0.9806258],"study_design_scores_gemma":[0.004162579,0.0001526571,0.3811086,0.0006941863,0.0001183808,0.0003180034,0.002861196,0.4079435,0.007271327,0.000650932,0.193257,0.00146166],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01168622,0.0002196979,0.9780077,0.001228764,0.0005768252,0.001655365,0.0008840786,0.0006674458,0.005073949],"genre_scores_gemma":[0.9968072,0.00001910277,0.001428871,0.00004510747,0.0003376621,0.001030962,0.00004529612,0.00001143898,0.0002743419],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.985121,"threshold_uncertainty_score":0.8763077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04129495468710166,"score_gpt":0.2680840172572439,"score_spread":0.2267890625701423,"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."}}