{"id":"W4236062305","doi":"10.1111/gwmr.12273","title":"Table of Contents","year":2019,"lang":"en","type":"article","venue":"Groundwater Monitoring & Remediation","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Table (database); Computer science; Citation; Information retrieval; Table of contents; World Wide Web; Database","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":[0.0002662372,0.00009997181,0.0001586893,0.00004157846,0.00004647593,0.0000289603,0.0001567028,0.00005448376,0.0002429725],"category_scores_gemma":[0.00001802361,0.00008796892,0.00005519975,0.0001946537,0.00003149778,0.0003212725,0.00008021168,0.00007307633,0.0007118237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009643425,"about_ca_system_score_gemma":0.000002890802,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001419218,"about_ca_topic_score_gemma":0.000001714105,"domain_scores_codex":[0.9988469,0.00004573806,0.0002572017,0.0002232572,0.0004162664,0.0002106662],"domain_scores_gemma":[0.9995313,0.0000269421,0.0001165164,0.0002519319,0.00001948825,0.00005388013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000006232016,0.00003315345,0.6948198,0.00001099031,0.00001196319,4.018714e-7,0.0003343809,0.0003047762,0.3033459,0.000004535377,0.00005113475,0.001076682],"study_design_scores_gemma":[0.0003116999,0.00006512554,0.3554322,0.00002988053,0.00002244213,5.959668e-7,0.00016457,0.0001160433,0.6413264,0.0001219676,0.002263914,0.0001451884],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977846,0.00001398429,0.0002596424,0.00005635381,0.001096653,0.00009502793,0.000001088247,0.00003869091,0.0006539779],"genre_scores_gemma":[0.995774,0.000008680821,0.0004807514,0.00000448014,0.0002392486,0.00000765591,0.000009251686,0.0000115252,0.003464395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3393876,"threshold_uncertainty_score":0.9149291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01922036315456237,"score_gpt":0.2359905601957868,"score_spread":0.2167701970412244,"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."}}