{"id":"W4318041446","doi":"10.7557/cage.6835","title":"Annual Report 2016","year":2023,"lang":"en","type":"article","venue":"CAGE – Centre for Arctic Gas Hydrate Environment and Climate Report Series","topic":"Offshore Engineering and Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Arctic Eider Society","funders":"","keywords":"Excellence; Relevance (law); Work (physics); Enhanced Data Rates for GSM Evolution; Quality (philosophy); Engineering management; Computer science; Engineering; Political science; Mechanical engineering; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002645139,0.0002882415,0.0002879167,0.0001026482,0.0001493984,0.00003577328,0.00009151472,0.0001316311,0.00004881793],"category_scores_gemma":[0.00006082921,0.0002721225,0.00009120034,0.0001135818,0.0001193839,0.0002321996,0.0001081365,0.0001295017,0.00006861903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006488641,"about_ca_system_score_gemma":0.000007484598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003502205,"about_ca_topic_score_gemma":0.00000339038,"domain_scores_codex":[0.998437,0.000006561194,0.0004254841,0.0003697013,0.0001660424,0.0005952372],"domain_scores_gemma":[0.9993403,0.0000421963,0.00008057092,0.000419805,0.00001336965,0.0001037363],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004510418,0.0005848873,0.3439771,0.01230445,0.003325885,0.08089959,0.01086974,0.2205691,0.07423007,0.007448081,0.1701605,0.07517962],"study_design_scores_gemma":[0.0007563462,0.0001871909,0.01794855,0.0002000126,0.0002112806,0.003294705,0.003533585,0.006812476,0.01721274,0.00166659,0.9468339,0.001342608],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932773,0.0005760206,0.0003445725,0.0008372865,0.0009640667,0.0004648273,0.0001853187,0.002444907,0.0009056621],"genre_scores_gemma":[0.9851177,0.007275193,0.0008768333,0.000006911744,0.000128172,0.0001008677,0.0004360335,0.0001019345,0.005956365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7766734,"threshold_uncertainty_score":0.9999731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005855013756574956,"score_gpt":0.1844824361908754,"score_spread":0.1786274224343005,"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."}}