{"id":"W4389335818","doi":"10.1039/d3cp05555h","title":"<i>In situ</i> monitoring of mechanochemical MOF formation by NMR relaxation time correlation","year":2023,"lang":"en","type":"article","venue":"Physical Chemistry Chemical Physics","topic":"Metal-Organic Frameworks: Synthesis and Applications","field":"Chemistry","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; New Brunswick Innovation Foundation","keywords":"Metal-organic framework; Relaxation (psychology); In situ; Nuclear magnetic resonance; Materials science; Chemistry; Chemical physics; Physical chemistry; Organic chemistry; 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":[0.0001851101,0.0002901039,0.0001700456,0.0002216251,0.0002264018,0.0003517401,0.0005071739,0.000477172,0.001174624],"category_scores_gemma":[0.000319509,0.0001195793,0.0001016631,0.000178169,0.0004024371,0.0004227818,0.0002307303,0.0005057337,0.0002523087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002299104,"about_ca_system_score_gemma":0.0001342964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006619829,"about_ca_topic_score_gemma":0.001109054,"domain_scores_codex":[0.9998837,0.00001854841,0.000006123837,0.00003755798,0.00002950181,0.00002463991],"domain_scores_gemma":[0.999858,0.00003869089,0.0000495727,0.00001829231,0.00002455654,0.00001078281],"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":[0.00003911679,0.00001252379,0.0001245292,0.00005173018,0.000003326802,0.00003748231,0.00001132074,0.0001319539,0.9957628,0.0004722762,0.0002410423,0.003111779],"study_design_scores_gemma":[0.000002515168,0.0000355271,0.0002231746,0.000001455126,0.000002525193,0.00006800206,0.000007882478,0.001298324,0.9969991,0.00006036998,0.001296453,0.000004755908],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7431811,0.003728697,0.2331107,0.0016442,0.0004377289,0.0001406978,0.001275675,0.001508555,0.01497252],"genre_scores_gemma":[0.8892062,0.001452503,0.1050584,0.0003906314,0.0001452784,0.00009312864,0.0004040824,0.00008135175,0.003168374],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001174624,"threshold_uncertainty_score":0.003929496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0109291542796511,"score_gpt":0.2365738705885422,"score_spread":0.2256447163088911,"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."}}