{"id":"W4411078855","doi":"10.1016/j.precamres.2025.107832","title":"Petrogenesis of TTG gneisses from the Liaodong Bay Depression, Bohai Sea Basin: implications for the late Neoarchean tectonic evolution of the eastern North China Craton","year":2025,"lang":"en","type":"article","venue":"Precambrian Research","topic":"Geological and Geochemical Analysis","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Chengdu University of Technology; China Postdoctoral Science Foundation; National Natural Science Foundation of China; Sichuan Province Science and Technology Support Program; Ministry of Natural Resources","keywords":"Geology; Petrogenesis; Craton; Tectonics; Geochemistry; Gneiss; Bay; Structural basin; Earth science; China; Geomorphology; Paleontology; Oceanography; Metamorphic rock; Archaeology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0009713341,0.0001115033,0.0001948531,0.00006615475,0.000704009,0.00004704756,0.001105093,0.00006656394,0.0004673433],"category_scores_gemma":[0.000803693,0.00004778385,0.0002161113,0.001233138,0.00048172,0.00005866033,0.0001707398,0.000286093,0.00001214253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001025284,"about_ca_system_score_gemma":0.0001625184,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02714441,"about_ca_topic_score_gemma":0.04009579,"domain_scores_codex":[0.9981862,0.0005129676,0.0003024521,0.0002770227,0.0003585104,0.0003628787],"domain_scores_gemma":[0.9964187,0.002488238,0.00009867221,0.0006511062,0.0002748979,0.00006835125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006920097,0.00002974238,0.9740177,0.00002413046,0.00007654863,6.031934e-8,0.00007893449,0.0007400304,0.0005746361,0.00009477584,0.0003379852,0.02395624],"study_design_scores_gemma":[0.0001340977,0.00003522371,0.9763862,0.00003630908,0.00006550273,3.293482e-7,0.0001432821,0.01282784,0.002031337,0.007793454,0.0004931369,0.0000532515],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824052,0.003164196,0.0004639339,0.01192529,0.00005377914,0.0005395329,0.0004563312,0.00001177375,0.0009799441],"genre_scores_gemma":[0.9988652,0.0001224064,0.00006541807,0.0000626338,0.00005208412,0.00003025,0.00006013989,0.000002597407,0.0007392309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02390299,"threshold_uncertainty_score":0.9793339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0329398572569182,"score_gpt":0.282816108404858,"score_spread":0.2498762511479398,"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."}}