{"id":"W4244510541","doi":"10.1063/1.5027273.1","title":"10.1063/1.5027273.1","year":2018,"lang":"en","type":"dataset","venue":"Default Digital Object Group","topic":"Analytical Methods in Pharmaceuticals","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Supercontinuum; Hyperspectral imaging; Broadband; Materials science; Microsecond; Optics; Dwell time; Pixel; Optoelectronics; Computer science; Physics; Artificial intelligence; Wavelength; Photonic-crystal fiber","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004029243,0.001068068,0.00118933,0.0002056833,0.000165028,0.0006960024,0.00178241,0.00131359,0.08153715],"category_scores_gemma":[0.003390323,0.0009920001,0.0006927866,0.0004273187,0.0007784942,0.0004401937,0.0009840133,0.001451531,0.03137504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002866238,"about_ca_system_score_gemma":0.0001272053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002375305,"about_ca_topic_score_gemma":0.000006989923,"domain_scores_codex":[0.9950988,0.00007442712,0.001057575,0.001419066,0.001142227,0.001207951],"domain_scores_gemma":[0.9953065,0.001307661,0.0004160353,0.002085118,0.0002067536,0.0006779344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001366983,0.0003161164,0.000004593931,0.0005189814,0.0003305026,0.000216347,0.000004053933,2.38807e-7,0.00006933993,0.00003625434,0.9906725,0.007694342],"study_design_scores_gemma":[0.0005376962,0.0001232398,0.000001376988,0.0002354366,0.0003519562,0.0000870912,0.00001308732,0.00005651235,0.0008382083,0.001105734,0.9954987,0.001150958],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000325114,0.0002543814,0.00009284821,0.00003133835,0.0004123685,0.0001514478,0.8949856,0.0002978001,0.1037417],"genre_scores_gemma":[0.0001382667,0.00006509296,0.0005933765,0.0003783024,0.002509238,0.0000716412,0.9755507,0.0001496043,0.02054381],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08319793,"threshold_uncertainty_score":0.9999829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03110832694753691,"score_gpt":0.3460825775915615,"score_spread":0.3149742506440246,"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."}}