{"id":"W4388757087","doi":"10.1109/lsens.2023.3333657","title":"IEEE Sensors Council Information","year":2023,"lang":"en","type":"article","venue":"IEEE Sensors Letters","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Information retrieval","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002324028,0.001497627,0.001481746,0.003375791,0.001461248,0.00325384,0.002192582,0.002848169,0.5202152],"category_scores_gemma":[0.005780973,0.0009621397,0.0006646395,0.002645373,0.0005321078,0.002812077,0.002150925,0.0026795,0.4165829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001206786,"about_ca_system_score_gemma":0.002569475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002668731,"about_ca_topic_score_gemma":0.005313387,"domain_scores_codex":[0.9976974,0.0003151902,0.00008967059,0.0002559074,0.00149268,0.0001491313],"domain_scores_gemma":[0.996194,0.0005251308,0.0001478288,0.0007836351,0.002090762,0.0002585577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007180612,0.00004012695,0.00008805651,0.000211003,0.000007163886,0.00002573661,0.00001660468,0.0003362337,0.001332077,0.004306887,0.89661,0.09695429],"study_design_scores_gemma":[0.00001343416,0.00002464371,0.0001819646,0.00006494697,0.000007536498,0.00004523672,0.00001685947,0.0008656367,0.001495736,0.002332021,0.9949381,0.00001388049],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0009076961,0.004625926,0.03633003,0.00687964,0.009521027,0.0006564439,0.0187183,0.006766073,0.9155948],"genre_scores_gemma":[0.008179198,0.004664435,0.009613336,0.002386801,0.001240798,0.0006848701,0.02234179,0.001869555,0.9490191],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4797848,"threshold_uncertainty_score":0.6843548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06568098960133949,"score_gpt":0.1987921485464502,"score_spread":0.1331111589451107,"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."}}