{"id":"W2773448793","doi":"10.3997/2214-4609-pdb.241.difrancesco_paper1","title":"Gravity Gradiometry – Today and Tomorrow","year":2009,"lang":"en","type":"article","venue":"11th SAGA Biennial Technical Meeting and Exhibition","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Scope (computer science); Software deployment; Computer science; Order (exchange); Data science; Operations research; Engineering; Business; Software engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0005666298,0.0001438517,0.0001834319,0.0000964542,0.0002660542,0.00009029994,0.00007349751,0.0001056964,0.00002721271],"category_scores_gemma":[0.00009104158,0.0001230658,0.0000428775,0.0002853326,0.00008675182,0.0001442651,0.00001206845,0.0001779046,0.00001567218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004593927,"about_ca_system_score_gemma":0.00001100685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004589382,"about_ca_topic_score_gemma":0.0001767113,"domain_scores_codex":[0.9988598,0.00005678318,0.0001937113,0.0003281978,0.0002700013,0.0002914686],"domain_scores_gemma":[0.9995378,0.00005929249,0.0000639401,0.0001245426,0.00003297389,0.0001814218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001782248,0.0001866574,0.2913944,0.00007825843,0.00001677952,0.00003864792,0.0001837889,0.00004075434,0.04888974,0.001771113,0.00114951,0.6560722],"study_design_scores_gemma":[0.0003775163,0.0004504723,0.9746588,0.00009099587,0.00002190676,0.00003709347,0.00002617596,0.0002724536,0.0009802479,0.02199266,0.0008452195,0.0002464335],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939897,0.000412046,0.00008456001,0.0007487935,0.0001188652,0.0001396096,0.00002408383,0.0001046453,0.004377693],"genre_scores_gemma":[0.9982783,0.00008621331,0.001095903,0.0003040236,0.0001623568,7.678374e-7,0.00004727353,0.000002573307,0.00002265292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6832645,"threshold_uncertainty_score":0.5018479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01770891269870256,"score_gpt":0.2278767972978896,"score_spread":0.210167884599187,"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."}}