{"id":"W2969254690","doi":"10.1039/c9ja00203k","title":"Application of X-ray photoelectron spectroscopy to examine surface chemistry of cancellous bone and medullary contents to refine bone sample selection for nuclear DNA analysis","year":2019,"lang":"en","type":"article","venue":"Journal of Analytical Atomic Spectrometry","topic":"Bone health and treatments","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saskatoon Medical Imaging; University of Saskatchewan","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; University of Akron; University of Saskatchewan; Canadian Light Source","keywords":"X-ray photoelectron spectroscopy; Cancellous bone; Chemistry; Medullary cavity; Infiltration (HVAC); Selection (genetic algorithm); Elemental analysis; Analytical Chemistry (journal); Materials science; Environmental chemistry; Nuclear magnetic resonance; Inorganic chemistry; Anatomy; Composite material; Computer science; Biology","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":[0.000422714,0.000200196,0.001298928,0.0005095545,0.00003384091,0.000009172649,0.00008411887,0.0001226683,0.0001798493],"category_scores_gemma":[0.000235696,0.0001729335,0.0002838573,0.001545803,0.00003985704,0.00005365055,0.0000280367,0.0002313105,0.000005512121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004969665,"about_ca_system_score_gemma":0.0001318157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004819765,"about_ca_topic_score_gemma":0.00003695096,"domain_scores_codex":[0.9978824,0.0000238289,0.0009687964,0.0003135675,0.0004475517,0.000363869],"domain_scores_gemma":[0.9981511,0.0001798372,0.0005854083,0.0002580171,0.000348792,0.0004768763],"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":[0.004135071,0.0006022645,0.09442197,0.0003228763,0.001403875,0.000005737697,0.00005348318,0.00009420302,0.8981808,0.00006430167,0.0001994965,0.0005159586],"study_design_scores_gemma":[0.009597999,0.0104289,0.2375004,0.0002677483,0.005678837,0.0003266867,0.0002291481,0.01673272,0.717405,0.0002374532,0.001167697,0.0004274792],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925844,0.0003473361,0.005485588,0.0008513824,0.00003371073,0.000539735,0.00003977372,0.00001021436,0.0001078507],"genre_scores_gemma":[0.9859611,0.0001325905,0.01337518,0.0001813324,0.00006777784,0.000003011872,0.00002113221,0.0000295876,0.0002282202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1807758,"threshold_uncertainty_score":0.7052022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009454313407176382,"score_gpt":0.2815015909359392,"score_spread":0.2720472775287628,"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."}}