{"id":"W7002161030","doi":"","title":"Maritime distress and safety communications in Canada","year":2001,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Distress; Marine safety; Government (linguistics); Occupational safety and health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001102836,0.0002053899,0.0002346056,0.0000343534,0.00003921149,0.00001819718,0.0003625674,0.000228495,0.03397389],"category_scores_gemma":[0.00009567248,0.0002189886,0.00003887761,0.000005926417,0.0001078657,1.719058e-8,0.000245738,0.0002167679,0.0001387747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005546829,"about_ca_system_score_gemma":0.0001089322,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8216301,"about_ca_topic_score_gemma":0.9530455,"domain_scores_codex":[0.999006,0.00006090849,0.0004631185,0.000117921,0.0001640209,0.000188037],"domain_scores_gemma":[0.9989664,0.00003500798,0.0003200979,0.0005606475,0.00004662819,0.00007121434],"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":[0.00003338571,0.00001253115,0.0002993276,0.0002089935,0.00002640924,0.000003158226,0.00001861496,0.0001283637,3.79244e-7,0.00001476456,0.9968156,0.002438488],"study_design_scores_gemma":[0.0003696306,0.00003762258,0.0001993766,0.0001254898,0.00001309718,0.00004750423,0.00008093581,0.0001187875,0.00000305946,0.000001212233,0.9987833,0.0002199502],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000109801,0.0006298777,0.000001257388,0.0001653734,0.00006210703,0.0002300837,0.0002950849,0.00001578333,0.9984906],"genre_scores_gemma":[0.00328837,0.002037187,0.001648087,0.0002439542,0.00003799972,0.00000905129,0.001322935,0.00005939249,0.991353],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1314154,"threshold_uncertainty_score":0.9669092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003823435903948632,"score_gpt":0.1892749091095861,"score_spread":0.1854514732056375,"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."}}