{"id":"W6887845237","doi":"10.17632/9h3vjvn2ms.1","title":"2-D and 3-D Geodynamic modoelling results: Rheological inheritance and rift segmentation in the Labrador Sea","year":2020,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Geological and Geochemical Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rift; Lithosphere; Margin (machine learning); Continental margin; Shield; Segmentation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007454977,0.001580097,0.0008188449,0.002644894,0.0008170308,0.001671824,0.002515811,0.001112788,0.01235253],"category_scores_gemma":[0.002179891,0.0005017613,0.001375628,0.003430206,0.0005609845,0.0005742238,0.001319348,0.001009189,0.01056664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00196973,"about_ca_system_score_gemma":0.002254457,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3842176,"about_ca_topic_score_gemma":0.5521314,"domain_scores_codex":[0.9994519,0.0000628585,0.00003803714,0.0001450177,0.000152769,0.0001494605],"domain_scores_gemma":[0.9991645,0.0001390026,0.00006721064,0.0002283082,0.000287049,0.0001140348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004681904,0.0002659071,0.03078849,0.001174067,0.0003688949,0.0003833383,0.0005372145,0.01940555,0.001984616,0.00204803,0.9203063,0.0222693],"study_design_scores_gemma":[0.0009738508,0.00008878507,0.1717107,0.000594958,0.0001886963,0.0002843809,0.00132893,0.04149384,0.004250108,0.002638085,0.7762229,0.0002248254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01332064,0.0001688716,0.000304713,0.0001793209,0.00003735301,0.00001912662,0.9820488,0.002377454,0.001543596],"genre_scores_gemma":[0.01217581,0.0000798059,0.001263051,0.00002699066,0.000008683306,0.00004012655,0.9854527,0.0001888929,0.0007638826],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6157824,"threshold_uncertainty_score":0.7639625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01843824606508999,"score_gpt":0.2209235687782791,"score_spread":0.2024853227131891,"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."}}