{"id":"W4406789273","doi":"10.1107/s1600576724011178","title":"Studying novel high-pressure phases in laser-shock-affected silicon using poly: an algorithm for spot-wise phase identification","year":2024,"lang":"en","type":"article","venue":"Journal of Applied Crystallography","topic":"Ion-surface interactions and analysis","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Australian Government","keywords":"Selected area diffraction; Silicon; Materials science; Diffraction; Polycrystalline silicon; Laser; Phase (matter); Electron diffraction; Amorphous silicon; Optics; Nanotechnology; Crystalline silicon; Optoelectronics; Chemistry; Transmission electron microscopy; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007255902,0.0008947043,0.0005819083,0.0008619866,0.0006178109,0.001082672,0.0009525919,0.0007747672,0.002081877],"category_scores_gemma":[0.001437755,0.0004112994,0.0004456858,0.0008103557,0.0005321735,0.0009682194,0.0007148103,0.0007115761,0.0006011938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000503781,"about_ca_system_score_gemma":0.001281122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002330759,"about_ca_topic_score_gemma":0.004938534,"domain_scores_codex":[0.9997101,0.00004963253,0.00002506366,0.00009785374,0.0000837905,0.00003359337],"domain_scores_gemma":[0.9991841,0.0003734532,0.0001332382,0.00009287837,0.0001804303,0.0000358761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001100634,0.000327082,0.01339961,0.0002720793,0.0001645447,0.0002569807,0.0002233764,0.1088912,0.1014969,0.007047146,0.002820493,0.764],"study_design_scores_gemma":[0.00003304855,0.00009049798,0.001360537,0.000006063287,0.00001587741,0.00008264119,0.00003378816,0.9709564,0.02439242,0.001552429,0.001463073,0.00001327602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04257711,0.00007494653,0.9538964,0.00006568906,0.00001696373,0.00008556005,0.00009404015,0.002469288,0.0007200067],"genre_scores_gemma":[0.101926,0.00005515398,0.8960799,0.00004628399,0.000009288374,0.0001595885,0.0002784472,0.0002117832,0.001233556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002330759,"threshold_uncertainty_score":0.006964564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01509603896210954,"score_gpt":0.2801545472245651,"score_spread":0.2650585082624556,"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."}}