{"id":"W2998466506","doi":"","title":"Status of the in situ 14C extraction system at CEREGE (Aix-en-Provence, France)","year":2019,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Nuclear Physics and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"ASTER","funders":"","keywords":"In situ; Extraction (chemistry); Computer science; Geology; Geography; Meteorology; Chemistry; Chromatography","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":[],"consensus_categories":[],"category_scores_codex":[0.00580978,0.001652953,0.001818845,0.002079242,0.001987451,0.003464902,0.002892803,0.002663045,0.01209353],"category_scores_gemma":[0.001618773,0.0007366145,0.0005672008,0.001524721,0.001237456,0.002143956,0.002514628,0.001260887,0.005961693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003021675,"about_ca_system_score_gemma":0.003372617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01370378,"about_ca_topic_score_gemma":0.01483936,"domain_scores_codex":[0.9975829,0.0003528127,0.00004769858,0.0006437219,0.001005583,0.0003672827],"domain_scores_gemma":[0.9986727,0.0002016345,0.0000999267,0.0002569564,0.0005344533,0.0002343759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00501454,0.0006273431,0.02641627,0.0009578044,0.0004805455,0.0004939438,0.001952673,0.004455728,0.7600672,0.005085719,0.01762735,0.1768209],"study_design_scores_gemma":[0.0009008194,0.001425492,0.0819211,0.0002234982,0.000414977,0.0007219471,0.0005276565,0.01503301,0.5801232,0.001979335,0.3164417,0.0002872087],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6299528,0.01358573,0.1660897,0.007105925,0.001198402,0.001719764,0.03355769,0.04240968,0.1043803],"genre_scores_gemma":[0.796174,0.002640942,0.1214672,0.001564905,0.0007701236,0.0007654108,0.01695812,0.004277106,0.05538227],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01370378,"threshold_uncertainty_score":0.04045695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008062012457939942,"score_gpt":0.2281983766036184,"score_spread":0.2201363641456785,"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."}}