{"id":"W1534383640","doi":"","title":"Morphological and magnetic characterization of electrodeposited magnetite","year":2005,"lang":"en","type":"dissertation","venue":"Memorial University Research Repository (Memorial University)","topic":"Minerals Flotation and Separation Techniques","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Dalhousie University","keywords":"Magnetite; Coercivity; Materials science; Crystallite; Electrolyte; Magnetic hysteresis; Antiferromagnetism; Overpotential; Inorganic chemistry; Chemical engineering; Metallurgy; Chemistry; Magnetization; Electrode; Electrochemistry; Physical chemistry; Magnetic field","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001022044,0.0001201164,0.00009526427,0.000276642,0.0002020552,0.0003591488,0.0002492772,0.000190975,0.001175214],"category_scores_gemma":[0.000253146,0.00009770711,0.0001090551,0.0002007515,0.0001219923,0.0001852158,0.00009731296,0.0001715197,0.0002345179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002158144,"about_ca_system_score_gemma":0.00007828963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006732881,"about_ca_topic_score_gemma":0.001066853,"domain_scores_codex":[0.999913,0.000004999368,0.000006380194,0.00002371764,0.00003836778,0.00001344411],"domain_scores_gemma":[0.9998628,0.00003118433,0.00002638613,0.00001458624,0.00005059457,0.00001448544],"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":[0.00001489509,0.000004280922,0.0001513203,0.00001611811,9.925834e-7,0.00003883796,0.00001800926,0.00004286308,0.9985546,0.00003426585,0.00001730618,0.001106523],"study_design_scores_gemma":[0.00000300528,0.00003584558,0.003174876,0.000003175298,0.000003421496,0.0001048178,0.00002931621,0.00052035,0.9951496,0.0000148569,0.0009586577,0.000002163289],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883077,0.000448464,0.006319934,0.00006423892,0.00002061387,0.00003069984,0.0005712978,0.0001301321,0.004106967],"genre_scores_gemma":[0.9876856,0.0003294206,0.006834666,0.00003644951,0.000009471191,0.00003649285,0.0007519409,0.00008213359,0.004233881],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001175214,"threshold_uncertainty_score":0.003931522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01430243020565146,"score_gpt":0.2465135429230619,"score_spread":0.2322111127174105,"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."}}